Various epigenetic modulators and their functions.
\r\n\tIn the maintenance and conservation of our planet's biodiversity, knowledge of current biogeographical patterns, speciation or invasion processes, flora, fauna, natural history, and ecology have outstanding importance. Many areas of biodiversity are still completely undiscovered nowadays. The ecological impacts of global climate change, urbanization, overpopulation, environmental pollution, deforestation, land cover and land-use changes also have a significant impact on biodiversity, flora, and fauna, through biogeographical patterns.
\r\n\tThe management tools, methods and processes (as applied ecological aspects) of Protected Areas and National Parks are a very important part of conservation policy. I am sure that this book will be very useful for everybody who would like to get some insight into the recent problems of biodiversity research, ecology and conservation biology also from practical or theoretical viewpoints.
Many heuristics and metaheuristics (problem‐independent algorithmic framework) have been successfully applied for decision and optimization problems. However, there are difficulties in using the already‐existing algorithms for new problems or even for new instances of a similar problem. Typically, one needs a time‐consuming phase for parameters tuning. The parameters, are often not well‐described and do not allow for solving the problem at a satisfactory level (producing satisfactory solutions). Thus, in many cases, one needs to construct new algorithms to solve particular instances. Recently, there have been attempts to automate the process of designing methods to learn the tuning of the parameters. The basic idea is to develop a method which is general and operates on small moves and learns which moves should be applied at each stage of the solving process.
\nThe term hyper‐heuristics was first used by Cowling et al. in 2001 [1] for the sales summit problem and refers to a method which does not use the problem‐specific information other than a set of simple knowledge poor heuristics which are easy to implement. Between the set of simple low‐level heuristics and high‐level heuristics, there exists a domain barrier, which does not allow to pass the information about the problem domain. A high‐level hyper‐heuristic uses performance indicators when a low‐level heuristics is called (indicators are not specific to the problem) in order to decide which heuristics should be chosen at a particular time point in the search space. However, the ideas behind hyper‐heuristic are not new to the scientific community, and their roots trace back to 1963 and spanned several areas: computer science, artificial intelligence, and operational research. In 1963, Fisher and Thompson [2] showed that combining scheduling rules, known as dispatching or priority rules, is better when they are combined rather than used separately. In 1990s, the ideas were further explored. Storer et al. [3] designed a few fast problem‐specific heuristics and defined neighborhoods within the search space. The approach could be applied with any scheduling objective and was tested for the job shop scheduling problems with the minimum makespan objective. In Fang et al. [4], a genetic algorithm (GA) was developed which tried to avoid difficulties in representing a solution as a chromosome, which is needed by the GA. The proposed method searches abstract regions of the solution space and then uses another method which converts the points generated by the GA into candidate solutions. Drechsler and Becker [5] presented a GA which first, based on benchmark examples, learns a good sequence of basic optimization modules (simple methods) and then applies it to instances of a given problem (computer‐aided design of integrated circuits).
\nSome examples of automated parameter tuning can also be considered as a basis for hyper‐heuristics. In Ref. [6], one evolutionary algorithm was used to tune the second one, which solved a particular problem. Also, some approaches of self‐adaptation in the parameter tuning of the evolutionary algorithms were summarized in the survey [7].
\nIn the area of machine learning, the idea of choosing the best algorithm for a given problem was first posed by Rice [8]. Following this idea, several projects created specialized systems to help to select/recommend the best method, as for example, Consultant‐2 [9] and Teacher (Techniques for the Automated Creation of Heuristics) [10]. Consultant‐2 was developed to support the machine learning toolbox. It integrates the knowledge of choosing the proper machine learning algorithms based on the nature of domain data and the domain experts’ knowledge of preprocessing and manipulating the data, in order to use the system without directly involving the specialists. On the other hand, Teacher was designed as a system for learning and generalizing heuristics used in problem‐solving. Despite the lack of or little domain knowledge, the system was able to improve the existing heuristic methods. The Teacher was successfully applied in the area of process mapping, load balancing, routing, and testing.
\nThe above examples show that the term hyper‐heuristics, although did not appear before the year 2000, had circulated in the literature for quite a long time. Since then, the term was used, and the idea further developed in many different problem domains [11, 12].
\nThe methods often used in the context of hyper‐heuristics have strong connections with biology. However, the flow of ideas between biology and operational research works in both directions. Observations of nature provide the basis for designing algorithms: many evolutionary and genetic algorithms were used as (hyper‐)heuristics to solve combinatorial optimization problems. On the other hand, operational research methods can help solving problems arising in the field of biology and resulted in creating a new area of Bioinformatics. Some examples of problems solved with the use of bioinformatics tools are DNA sequencing, DNA mapping, RNA structure prediction and protein folding. Moreover, mutual infiltration of the ideas of the two scientific domains can work in both directions just for a single problem. The DNA sequencing by hybridization (SBH) problem (further described in Section 4) in the ideal case was first defined as searching for a Hamiltonian path in a special graph [13], which is an NP‐hard problem. SBH was later modeled as the search for a Eulerian path that could be solved in polynomial time [14], which is the opposite of searching for a Hamiltonian path problem. Analysis of this phenomenon resulted in defining a new type of DNA graphs and showed why searching for a Hamiltonian and Eulerian path in these two types of graphs is equivalent [15]. For that particular problem, the operational research methods were used to solve the problem, while the analysis of SBH problem introduced a new type of graphs and gave an insight into the connections between easy and NP‐hard problems.
\nThe goal of this chapter is to show the connections between the areas of biology, computer science and operational research in the context of (hyper‐)heuristics search. Although some surveys on the meta and hyper‐heuristic search have been published [11, 12], here we focus mainly on the selected bio‐inspired problems solved with hyper‐heuristic methods. In the next section, the classification of hyper‐heuristic algorithms is presented. Section 3 describes different methods used in the hyper‐heuristic framework. The following section focuses on few biological problems successfully solved with hyper‐heuristics. In Section 5, we show that not all the problems could be solved with hyper‐heuristics and specially tailored‐to‐measure heuristics are needed. We also propose a small hint how hyper‐heuristic search could be incorporated in solving the DNA assembly problem. Section 6 summarizes and highlights a potentially interesting future research direction.
\nA hyper‐heuristic framework consists of a set of low‐level heuristics and a high‐level hyper‐heuristic algorithm. The latter evaluates the performance of low‐level heuristics and selects one of them to change the current solution. The performance can be measured as an increase in the objective function value, defined for the problem, but can also check the time of computations or the time a heuristic was last used. The hyper‐heuristic can process one (single point search) or multiple solutions at a time (multi‐point search). In the former, an initial candidate solution goes through a set of successive steps until it gets to the final solution. In the latter, utilized for the perturbative methods, a few solutions are processed in parallel, like for example in the AMALGAM approach, which operates on the population of solutions [16]. Apart from the selection of the low‐level heuristics, the acceptance mechanism seems to be crucial in the hyper‐heuristics research. The decision whether to accept or reject the new solution can be always the same for the same (
General scheme of how hyper‐heuristics work.
In Burke et al. [17], the definition of a hyper‐heuristic was further extended to
Classification of hyper‐heuristics (following Ref. [
According to the nature of the search space, we might have methodologies that
The second dimension corresponds to a learning mechanism which is used by a hyper‐heuristic algorithm. If the learning takes place while the algorithm is solving an instance of the problem than we say that there is an
In
There are some methods which do not fit strictly to the frames presented above but rather span across two or more categories. They use either selecting and generating methods [34] or perturbative and constructive heuristics [35].
\nLearning techniques are key/essential indicators of the quality of hyper‐heuristics. Good learning mechanisms impinge on obtaining better solutions and the possibility to reuse the hyper‐heuristic and this decrease software production costs. Low‐level heuristics are usually simple heuristics designed for a problem, but if used in a wrong order may not allow to get better solutions than when a single such heuristic is applied. Depending on the nature of the search space, different learning mechanisms were used. Below a few of the approaches are mentioned, some of them derived from the observations on biological evolution made by naturalist Charles Darwin. In his concept, the individuals in the population of one species are subject to the natural selection rules to fit the environment better. Among the fitting mechanisms, we can distinguish (i) crossover, reproducing of individuals in order to create a new one(s), (ii) mutation, random change of an individual in order to introduce diversity to the population, and (iii) selection of the best features in the population or in one individual. Biological evolution was an inspiration for developing bio‐inspired algorithms like evolutionary algorithms, genetic algorithms or genetic programming. All of them were utilized as hyper‐heuristics in different contexts of the nature of the search space. A few examples are mentioned in the following paragraphs.
\nIn the selection mechanism with the combination of constructive heuristics, commonly used local search–based hyper‐heuristics explore the solution space with the selected heuristics as widely as possible. A variable neighborhood search was used in the context of examination timetabling [18]. Tabu search‐based hyper‐heuristic was applied for the workforce scheduling problem [36] and course and exam timetabling [19]. Evolutionary or genetic algorithms were used for solving the vehicle routing problem [35] and bin packing of 2D elements [37].
\nIn case of perturbative low‐level heuristics, more commonly used are score‐based hyper‐heuristics. A choice function was introduced in Ref. [1] which evaluates each heuristic according to a score composed of three components: how well a heuristic performs, how well it performs when combined with another one, and the time elapsed since it was last used. A low‐level heuristic can be selected in four different ways (i)
The solution obtained by applying a low‐level heuristic might not always be improved. There are different strategies in accepting the solution in case of deterioration. ‘All accept’ always accepts the solution. Some other strategies accept a new solution with the probability that decreases with time: simulated annealing or Monte Carlo.
\nIn generating new heuristics, one usually involves genetic programming (GP). GP, similarly to evolutionary algorithms, borrows ideas from the theory of natural evolution to automatically produce programs [42]. It starts from a population of generated computer programs which are evaluated by the fitness function. Next, evolutionary components (selection, mutation, crossover) are applied to the individuals in the population and the strongest, i.e. the fittest ones, survive in the next generation. The difference between standard GP and the hyper‐heuristic GP is in the generality of the programs used. In the standard approach, the programs could be standard arithmetic operations, standard mathematical functions or logical functions, while in the hyper‐heuristic approach, the programs are rather abstract heuristics, independent of the problem domain. As the output from the GP, one gets new programs, which in standard approach could be direct solutions (i.e. modified mathematical formulas or arithmetic operations), but in the hyper‐heuristic approach, they need to be translated into solutions. Automatically generated heuristics can be
GP hyper‐heuristics were utilized to modify dispatching rules for the job shop scheduling problem ([43], as an example). Grammar‐based GP with graph coloring and slot allocation heuristics were applied to exam timetabling [24]. Many applications used GP to evolve heuristics also for the bin packing problem [27, 44] and traveling salesmen problem [25, 45].
\nThere is an interesting connection between the idea of reusable heuristics and transfer learning [46]. In both cases, one may observe the transfer of knowledge between different but related problem domains. However, in the first case, hyper‐heuristic is used to tune heuristics from one instance to another or to generate new heuristics, and in transfer learning training data of one problem may be used to potentially improve the results of a target learner on a data set from a different domain. Transfer learning is used mostly in cases when there is a lack of training data or they are too expensive to collect.
\nIn this section, a few examples are described in more details for which hyper‐heuristic methods were used to solve bio‐inspired problems. This field has not been explored deeply, and only a few attempts have been made so far. The difficulty here lies in the quality of the solution. For bio‐experts, it is often important that the solution is the optimum or very close to the optimum, not just ‘good enough’. Moreover, sometimes mathematical models cannot express biological problems well. The optimization function in the model may lead to a few solutions which are mathematically optimal but only one is biologically correct. Three main contributions from the literature are summarized below, one dealing with the longest common subsequence problem and two with the sequencing by hybridization problem.
\nThe longest Common Subsequence (LCS) problem amounts to find the longest string that is a subsequence of every string in a given set of strings. The subsequence here is not composed of consecutive letters in the string, but it can be achieved by deleting some of the characters from the string. The problem can be solved polynomially in the case of two strings, but in general, the problem is NP‐hard. The example of what the LCS problem is explained in Figure 3.
\nThe example of the LCS problem. For a given set of strings
The LCS problem is used in bioinformatics to compare sequences of molecules: DNA, RNA or proteins, in order to find homologies between sequences of organisms of different species. The homology helps to predict the function of unknown genes if their sequences are similar to those of known genes one may expect that the function is similar. The other applications of LCS can be found in text editing [47] or data compression [48], among others.
\nTabataba and Mousavi [49] proposed a hyper‐heuristic for the LCS problem. A beam search algorithm in its standard form is a tree‐based procedure. It starts from the initially empty solution and extends it by one letter in every iteration. All possible characters
The method was tested on random biologically inspired and real sequences of DNA and proteins of rats and viruses (
Sequencing by hybridization (SBH) is a method used for reading DNA sequences, nowadays not used any more due to high costs, but its concepts can be of value for other real‐world applications. It is composed of two phases, biological and computational experiments. The former utilizes a microarray chip to determine all the subsequences of an unknown DNA sequence, i.e. subsequences of a given length
SBH is composed of biological and computational experiments. In the first one (a), a microarray, containing all
In the ideal case, the problem is easy, while in the real experiments, two types of errors may occur which make the real problem NP hard. A negative error occurs when a
A hyper‐heuristic approach was first used to solve the SBH problem in Ref. [39]. The solution is represented as an ordered
The low‐level heuristics operate on the list and trash by moving elements from one set to another. In the basic approach, we can distinguish operations on single elements: insertion from trash to list, deletion from list to trash or shift–moves of the elements within the list; or operations on a cluster–a group of closely connected elements. A cluster can be shifted or deleted. An extended approach changed the encoding of the solution, by allowing elements from the spectrum to appear on the list twice, thus solving the problem of repetitions. Also, several new heuristics were proposed, with
A few hyper‐heuristics were proposed, namely a tabu search algorithm, choice function approaches (roulette, ranked, best and decomp), and a simulated annealing algorithm. In the first method, all moves were accepted, while the last method used the Monte Carlo approach which could reject a deteriorated solution with the probability that increased with the passed time. The results of the computational experiment showed that designing a good set of low‐level heuristics is very important, a good set could give good results for any tested hyper‐heuristics, even for a random roulette choice function, while an incorrectly composed set of primitive heuristics did not allow almost any algorithm to learn which heuristic to choose. The experiments on real DNA sequence instances pointed out two algorithms to be better than others: simulated annealing and the roulette choice function. In the comparison with other algorithms designed for that problem, the usage of elements from the spectrum in the solution was comparable with those obtained by hyper‐heuristics, while the similarity of the solution and the examined DNA sequence was superior for tailored‐to‐measure algorithms.
\nIn Ref. [50], again the DNA sequencing by hybridization problem was considered, but this time accompanied by other combinatorial problems: the knapsack problem, traveling salesman problem (TSP) and its two variants, namely, bottleneck TSP and prize collecting TSP. For these problems, a few hyper‐heuristics were implemented, similar to those presented in Section 4.2 and [39]. It is not new that the same hyper‐heuristic is used to solve problems in different domains. The novelty of the proposed approach was in modeling unified encoding of all the above problems, and implementing just one set of low‐level heuristics. The heuristics were independent from the problems; thus, a domain barrier was moved down toward problems (compare Figures 1 and 5).
\nIn the unified encoding of the hyper‐heuristic scheme there is just one set of low‐level heuristics for several problems, while in the standard scheme (
The solution for all the problems is represented as sequence
The proposed low‐level heuristics were simple moves, however, taking into account the specificity of the tested problems. Besides the low‐level heuristics previously proposed, insert, delete, swap, and shift, and four more were implemented: (i) replace an element from
Some hyper‐heuristics could distinguish, useless low‐level heuristics or ones leading to unfeasible solutions, and discard them from further computations. The overall results were ‘good enough’, but with the increase of algorithm’s generality, the quality of the obtained solution decreased a little in comparison to hyper‐heuristics from Ref. [39] and other tailored metaheuristics.
\nThe previous section presented a few bioinformatics problems solved with hyper‐heuristics. Not many attempts have been made so far, due to the specificity of biological problems.
\nSequencing by hybridization is a method that did not stand the test of time, but ideas developed in this approach can be translated into the next level of reading DNA sequences, namely assembling. The explosion of new technology allows to directly read short DNA fragments, up to a few hundreds of molecules, and thus making the old‐fashioned and costly approaches, Sanger sequencing [51] and SBH, not useful anymore. The inputs to the assembly problem are these longer sequences merged in order to get a longer one of the size of a bacterial genome. In the ‘toy problem’ -SBH, the fragments are of a length of a dozen or so, and the solution sequence is a few hundred long, while for the assembly problem, DNA fragments are in the range 100–1000 molecules and are assembled into a million‐molecule sequence. Both problems can be modeled as searching for a path in the graph, where nodes represent short DNA fragments, and arcs connect overlapping nodes with the cost equal to the shift between the two neighboring fragments. However, in DNA assembly, one must allow mismatches in fragment overlapping, differences in fragment lengths, and the fact that fragments may come from two strands of DNA helix; thus, they are reverse and complementary (the example of the reverse complementary sequence is presented in Figure 6). Also, the number of input fragments differs, a few hundred for SBH and millions for assembly. Moreover, during the process of reading DNA fragments, some parts of the genome could be poorly covered by the fragments or even in some cases not covered at all. There might be a few reasons for that, one of them, for example, depends on the content of G and C letters in the fragment of the genome. Thus, the assembly problem becomes much more difficult than SBH, and we cannot say any more about the ‘ideal case’ and ‘easily solvable’ problem.
\nAn example of the reverse and complementary sequence. A DNA sequence is always read from 5′ end to 3′ end. Due to the complementarity rule, A on one strand is connected with T on the other, and G is connected with C. The following fragment of the DNA helix can be read as ‘accgacttgcga’ or ‘tcgcaagtcggt’.
The assembly problem is usually divided into three steps:
\nIn the first step, it is usually impossible to calculate the overlaps between each pair of fragments, due to a huge number of fragments and time limitations. In Step 2, instead of one path, the methods output few or more paths, because of sequencing errors, the lack of coverage, and the repetitions in the genome. The last step is the multiple sequence alignment problem, which again is not easily solvable. There are two main approaches to solve the DNA assembly problem. The first one, Overlap‐Layout‐Consensus (OLC), represents DNA fragments as nodes in the
Junctions in the graph complicate the assembly process. In order to simplify the figure, only the arcs with the smallest shift between the two nodes are given. Without additional information, it is difficult to state if the correct sequence should be composed of fragments ACD, ACE, BCD, or BCE. Thus, the methods usually cut the current path and output shorter fragments like AC or CE.
One may notice that the field of bioinformatics combinatorial optimization problems is not well explored in terms of hyper‐heuristic search. The assembly problem is just one example of many problems, where a hyper‐heuristic could be introduced. The question is if we are ready to allow a possible deterioration of the final solution by generalizing the search process. The other question is what is the most time‐consuming activity: understanding a bio problem, designing a model, or implementing a method? In the case of some problems, it is crucial to clearly understand the problem because omitting some of the details makes the solution unacceptable for bio‐experts. Hyper‐heuristics and especially low‐level heuristics should be developed to comply with all the restrictions and produce a feasible solution, which, unfortunately, in many cases may take as much time as implementing a ‘tailored‐to‐measure’ algorithm.
\nThe flow of ideas between biology, operational research, and computer science works in both directions. The ideas from the biological evolution serve as the basis of genetic algorithms and genetic programming. The operational research models and methods help to solve many problems arising in computational biology. Recently, an interesting cooperation between these two scientific areas has been observed in the behavior of the slime mold
We can observe a constant synergy between specialists from different areas. This synergy can also be found in the context of hyper‐heuristic methodology. It has been shown that hyper‐heuristics have been successfully involved in solving several combinatorial optimization problems. Also, a few attempts have been made to solve bio‐inspired problems: the longest common subsequence problem and sequencing by hybridization problem.
\nIn Section 5, a proposition how to employ hyper‐heuristic search also in solving the DNA assembly problem has been made. By allowing offline learning on some benchmark dataset, the method could distinguish the junctions of the path in the graph and react faster whether to extend or cut the current path.
\nA good learning mechanism incorporated into hyper‐heuristics is a key to increase the usage of hyper‐heuristics and to solve the problems in a competitive way to tailored‐to‐measure (meta)heuristics. In this context, the development of the tools for assessing hyper‐heuristics such as HyFlex [59] or Hyperion [60] may increase the usage of these types of methods.
\nThe author would like to thank J. Blazewicz, G. Felici and the anonymous referee for valuable remarks and the discussions which significantly improved the presentation of the paper.
\nThe research was partially supported by a Poznan University of Technology grant [09/91/DSPB/0600].
\nRegulation of gene expression is the ultimate criteria that decide the role of each player in all cellular pathways. Gene regulation occurs in the nucleus and cytoplasm at multiple levels such as chromatin conformation, transcription regulation, post-transcription regulation, regulation of translation, protein modification, and protein degradation. Regulation at transcription is one of the prominent mechanisms as it involves the so called ‘switching-on and switching-off’ of genes. Gene regulation is required for organisms not only for their routine growth and maintenance but also for survival during unfavourable conditions. In this context, epigenetic regulation is of much significance because it not only offers adaptive skills to the organisms under stress but also has the potential to be heritable, thereby contributing to transgenerational memory. Owing to lack of locomotion and vocabulary in plants, like their animal counter parts, it is imperative for them to survive in unfavourable conditions such as biotic and abiotic stress. Therefore, plants have evolved with an elaborate mechanism of gene regulation, especially epigenetic regulation. Researchers have deduced gene functions by adopting various approaches and the key findings in epigenetic regulation and transgenerational memory in plants during biotic stress are described in this chapter.
Promoters serve the function of a switch as they are the site for the binding of RNA polymerase and other transcription regulators. Promoters harbour
Epigenetic changes refer to all modifications or influences on the chromatin, except for changes in the DNA sequence [4, 5]. These changes if occurred in promoters or other regulatory regions can result in altered gene expression, thereby contributing to phenotype plasticity. Multiple factors can lead to epigenetic changes (Figure 1). Nucleotides in DNA, especially cytosine, undergo methylation/demethylation. In addition to methylation, histones can undergo other chemical modifications such as acetylation, phosphorylation, ubiquitylation, and sumoylation. Non-coding RNAs are involved in altering chromatin organisation and/or methylation of chromatin [6]. Replacement of histones by histone variants such as H3.3, H2A.X, and H2A.Z also influence chromatin organisation and gene expression [7, 8].
Multiple causes of epigenetic regulation.
Discoveries in various aspects of epigenetic regulation in plants provided a deeper perception of various pathways, including defence. Different approaches taken by researchers include the study of epigenetic regulation of defence genes directly under pathogen stress, whole epigenome analysis, and understanding of the regulation of epigenetic regulators and their influence on disease (Figure 2). In this chapter, the research done in understanding different aspects of epigenetic regulation during plant-pathogen interaction and defence is described. Epigenetic changes have the potential to be retained after multiple cell divisions of both mitosis and meiosis. Therefore, heritable epigenetic changes lead to an interesting phenomenon of transgenerational memory. Epigenetic changes play a crucial role in plants as they not only lack locomotion, but also the vocabulary mode of communication. Biotic/abiotic stress-induced epigenetic changes have often generated plants and even their offsprings, with enhanced stress resistance. Such aspects are also elaborated in this chapter.
Various paths chosen by researchers to understand the involvement of epigenetic regulation of plant defence, including the transgenerational memory of defence. The dotted arrows indicate the involvement of epigenetic modulations in that step.
Pathogen stress is well known to alter the expression of numerous genes, belonging to several pathways, including those involved in defence, in plants. Interestingly, there are reports revealing the involvement of pathogen stress in altering the epigenetic status of various defence genes. For example, infection by
Though regulation of defence genes was known to be modulated by many TFs as mentioned earlier in this chapter, it is interesting to note that epigenetic regulation is involved in modulating these modulators. For example, promoters of three WRKY TFs, WRKY29, WRKY6, and WRKY53 underwent histone methylation and acetylation under biotic stress conditions and some of these modifications facilitated gene expression in primed plants [13].
About 130 genes are known to be involved in epigenetic regulation in plants [14]. We selected 60 genes involved in DNA and histone methylation (Table 1) and looked whether there are any previous reports on their expressions in the eFP Browser (
No. | Genes names and category | Function | References | |
---|---|---|---|---|
1. | Plant DNA methyltransferase | [15] | ||
2. | Maintenance of CHH methylation | |||
3. | A chromomethylase involved in methylating cytosine at non-CG sites | |||
4. | Gene silencing and maintenance of DNA methylation | |||
5. | Phosphate (Pi) homeostasis during DNA and histone methylation | [16] | ||
6. | Maintenance of CG and CHG methylation | [17] | ||
7. | Acts along with DME | |||
8. | Catalyses the release of 5-methylcytosine (5-meC) from DNA by a glycosylase/lyase mechanism | |||
9. | Maintains DNA methylation in CHG context | [18] | ||
10. | Major trans acting locus affecting DNA methylation | |||
11. | Link between responses to DNA damage and epigenetic gene silencing | [19] | ||
12. | DNA repair and meiotic recombination | |||
13. | High level delays flowering unless treated with prolonged cold | [20] | ||
14. | Encodes a histone 3 lysine 9 specific methyltransferase involved in the maintenance of DNA methylation | |||
15. | Required for posttranscriptional gene silencing | [21] | ||
16. | Normal RNA directed DNA methylation at non CG methylation sites and transgene silencing | |||
17. | Prevents the transmission of stress-induced transcriptional changes to progeny of the stressed plants | |||
18. | Prevents ectopic 3′ end processing of mRNA in atypically long introns containing T-DNA sequences | [22] | ||
19. | Encodes RNA-dependent RNA polymerase that is required for endogenous siRNA (but not miRNA) formation | |||
20. | Encodes a ribonuclease III family protein that is required for endogenous RDR2-dependent siRNA formation | |||
21. | SiRNA mediated gene silencing, CpNpG and CpHpH methylation | |||
22. | encodes a shared subunit of RNA polymerase IV and V | |||
23. | A putative DNA methyl transferase with rearranged catalytic domains | |||
24. | Important for DNA methylation and transcriptional gene silencing | |||
25. | Encodes a Dicer-like protein that functions in the antiviral silencing response | |||
26. | Encodes an RNaseIII-like enzyme that catalyses processing of trans-acting siRNA precursors | |||
27. | Encodes transcriptional regulator that promotes the transition to flowering, T DNA shows high methylation | |||
28. | Required for epigenetic maintenance of the vernalized state | [23] | ||
29. | Encodes a SET domain protein that is involved in epigenetic regulation | |||
30. | Has a SET domain for methyltransferase activity and is involved in the stable transcriptional silencing of target genes | |||
31. | Involved in centromere heterochromatisation, CG methylation | [24] | ||
32. | Activates the expression of AtWRKY70 epigenetically by nucleosomal histone H3K4 trimethylations | [25] | ||
33. | ATX1 leads to nucleosomal histone H3K4 trimethylations that activate AtWRKY70, which in turn activates | |||
34. | Histone methylations at the AtWRKY40 promoter activate the SA-dependent pathway to control plant immunity | |||
35. | Epigenetically influences systemic-acquired-resistance induced expression of AtWRKY29 and AtWRKY6 through histone modifications at their promoters | |||
36. | Leads to H3K4me2 and H3K4me3 methylation that epigenetically regulates AtWRKY53 to mediate leaf senescence responses | [26] | ||
37. | Histone methyl transferase activity and maintenance of H3 mK9 | |||
38. | Binds to methylated cytosine of CG, CNN, CNG | |||
39. | Control of replication of transposable elements and repeated sequences | [27] | ||
40. | Control of replication of transposable elements and repeated sequences | |||
41. | Maintains vegetative development, encodes a putative transcriptional regulator | [28] | ||
42. | Maintains vegetative development, encodes a polycomb group | |||
43. | Maintains gene silencing via histone modification | |||
44. | Maintains gene silencing via histone modification | |||
45. | Epigenetic maintenance of reproductive development | [29] | ||
46. | Gene involved in plant response to pathogen | [9] | ||
47. | Histone methyltransferase involved in di and tri-methylation of ‘Lys-36’ of histone H3 (H3K36me2 and H3K36me3) | |||
48. | Histone-lysine N-methyl transferase activity | |||
49. | Contributes to plant fitness like biomass, carbon fixation by influencing circadian clock period. | [21] | ||
50. | Essential component of a temperature-sensitive circadian system | |||
51 | Essential component of a temperature-sensitive circadian system | |||
52 | Necessary component for bacterial resistance. | |||
53. | One of the four closely related | [24] | ||
54. | Putative role in cell fate determination. Involved in the control of leaf morphogenesis. | |||
55. | Has a SET domain for methyltransferase activity and is involved in the stable transcriptional silencing of target genes. | |||
56. | Encodes a polycomb group of protein | |||
57. | Contains a SET domain which is known to be involved in modification of histone tails by methylation | |||
58. | SET domain, histone methylation | |||
59. | Encodes a type I protein arginine methyltransferase | |||
60. | Encodes a type I protein arginine methyltransferase |
Various epigenetic modulators and their functions.
Like any other pathway in organisms, epigenetic regulation is also maintained by many key players. There are reports that many such epigenetic regulators are directly associated with the expression of many defence genes as, observed in various loss-of-function mutant plants. JmjC DOMAIN-CONTAINING PROTEIN 27 (JMJ27), an
Using the
There are several reports confirming that various epigenetic regulators are directly involved in either providing immunity to plants or, to render the plants susceptible to various stresses. For instance, studies on
Biotic stress such as microbes and herbivory have induced loci-specific as well global epigenetic changes, both at DNA and histone levels. Infection of
Nematode-associated molecular patterns from different nematode species and bacterial pathogen-associated molecular pattern flg22 induced global DNA hypomethylation in rice and tomato plants [50]. Hypomethylation was more common at CHH and not CG or CHG nucleotides in these plants. While herbivory due to an insect
Open chromatin is an indication of epigenetic changes such as histone acetylation, which loosen chromatin. About 10,129 open chromatin sites associated with about 3025 genes, most of which also had enhanced expression, were induced in
A comparison of whole epigenomes in various
The beneficial fungus
There are several reports revealing the heritable nature of pathogen-induced epigenetic changes in plants [55, 56]. For example,
Transfer of epigenetic memory in plants.
The epiRILs lines of
Similarly, to pathogens, herbivory also induced transgenerational responses. For example herbivory due to caterpillars in
The close influence of pathogen stress on epigenetic modification of plant defence system and transgenerational memory offers an entire new array of promises for crop improvement. Approaches of whole epigenome studies under various conditions of biotic stress and resistance would unravel more aspects of the epigenetic regulation of host mechanisms. New avenues of epimutagenic studies that could serve as alternatives for methods that involve gene manipulations/mutations seem to be promising.
There are observations where application of certain chemicals such as SA, JA, methyl jasmonate, systemin, paraquat, abscisic acid, azelaic acid, and pipecolic acid on plants had resulted in enhanced resistance against pathogens, which could even be heritable [62, 63]. Even conditions of altered salinity, light, drought, and temperature had induced similar results [63]. Reports indicate that the action of some of these external factors involve epigenetic modifications in plants. For example, application of 1-isothiocyanato-4-methylsulfinylbutane on
While understanding of the DNA sequence conveyed what information is there in the genome and expression analysis conveyed what information is disseminated, research on epigenetics conveyed how the information is disseminated. While the entire genome of an organism needs to be sequenced only once to get the sequence information, epigenome has to be sequenced and studied multiple times, with multiple approaches, based on the regulatory aspects of relevance. Owing to the dynamic and reversible nature of epigenetic regulation and, phenotypic plasticity, epigenetic regulation can play a crucial role in improvising traits of agronomic importance, including plant defence. Functions of more epigenetic modulators need to be analysed that can tune the plants towards a favourable trait. The function of more epialleles needs to be identified for their application in developing enhanced resistance in plants. With the recent development of non-transgenic method of epigenome editing, epialleles of agronomic importance can be generated and deployed.
These Terms and Conditions outline the rules and regulations pertaining to the use of IntechOpen’s website www.intechopen.com and all the subdomains owned by IntechOpen located at 5 Princes Gate Court, London, SW7 2QJ, United Kingdom.
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\n\nThe following terminology applies to these Terms and Conditions, Privacy Statement, Disclaimer Notice, and any or all Agreements:
\n\n“Client”, “Customer”, “You” and “Your” refers to you, the person accessing this website and accepting the Company’s Terms and Conditions;
\n\n“The Company”, “Ourselves”, “We”, “Our” and “Us”, refers to our Company, IntechOpen;
\n\n“Party”, “Parties”, or “Us”, refers to both the Client and ourselves, or either the Client or ourselves.
\n\nAll Terms refer to the offer, acceptance, and consideration of payment necessary to provide assistance to the Client in the most appropriate manner, whether by formal meetings of a fixed duration, or by any other agreed means, for the express purpose of meeting the Client’s needs in respect of provision of the Company’s stated services/products, and in accordance with, and subject to, the prevailing laws of the United Kingdom.
\n\nAny use of the above terminology, or other words in the singular, plural, capitalization and/or he/she or they, are taken as interchangeable.
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pH, Fibre Degradation, and Microbiota According to the Diet",slug:"use-of-yeast-probiotics-in-ruminants-effects-and-mechanisms-of-action-on-rumen-ph-fibre-degradation-",totalDownloads:7902,totalCrossrefCites:17,totalDimensionsCites:38,abstract:null,book:{id:"2991",slug:"probiotic-in-animals",title:"Probiotic in Animals",fullTitle:"Probiotic in Animals"},signatures:"Frédérique Chaucheyras-Durand, Eric Chevaux, Cécile Martin and Evelyne Forano",authors:[{id:"151065",title:"Dr.",name:"Frederique",middleName:null,surname:"Chaucheyras-Durand",slug:"frederique-chaucheyras-durand",fullName:"Frederique Chaucheyras-Durand"},{id:"151068",title:"Mr.",name:"Eric",middleName:null,surname:"Chevaux",slug:"eric-chevaux",fullName:"Eric Chevaux"},{id:"151069",title:"Dr.",name:"Evelyne",middleName:null,surname:"Forano",slug:"evelyne-forano",fullName:"Evelyne Forano"},{id:"160177",title:"Dr.",name:"Cécile",middleName:null,surname:"Martin",slug:"cecile-martin",fullName:"Cécile 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Lemma",authors:[{id:"25594",title:"Dr.",name:"Alemayehu",middleName:null,surname:"Lemma",slug:"alemayehu-lemma",fullName:"Alemayehu Lemma"}]},{id:"57645",doi:"10.5772/intechopen.71780",title:"Antibiotics in Chilean Aquaculture: A Review",slug:"antibiotics-in-chilean-aquaculture-a-review",totalDownloads:1931,totalCrossrefCites:17,totalDimensionsCites:29,abstract:"Aquaculture in Chile has been practiced since the 1920s; however, it was not until the 1990s that aquaculture became an important sector here. Important species in Chilean aquaculture include salmonids, algae, mollusks, and turbot. Salmonids are the dominant species in Chilean aquaculture for both harvest volume and export value, their production reaching greater than 800-thousand tons in 2015. However, this growth has been accompanied by an increase in disease presence, requiring greater drug use to control. This increase in drug use is an environmental and public health concern for the authorities, the salmon industry itself, and the destination markets. In this chapter, we review the literature on drug use, antibiotic resistance, regulatory framework, and alternatives, with focus on Chile.",book:{id:"6179",slug:"antibiotic-use-in-animals",title:"Antibiotic Use in Animals",fullTitle:"Antibiotic Use in Animals"},signatures:"Ivonne Lozano, Nelson F. Díaz, Susana Muñoz and Carlos Riquelme",authors:[{id:"208847",title:"Dr.",name:"Ivonne",middleName:null,surname:"Lozano",slug:"ivonne-lozano",fullName:"Ivonne Lozano"},{id:"208895",title:"Dr.",name:"Nelson F.",middleName:null,surname:"Díaz",slug:"nelson-f.-diaz",fullName:"Nelson F. Díaz"},{id:"208897",title:"Dr.",name:"Carlos",middleName:null,surname:"Riquelme",slug:"carlos-riquelme",fullName:"Carlos Riquelme"},{id:"208898",title:"MSc.",name:"Susana",middleName:null,surname:"Muñoz",slug:"susana-munoz",fullName:"Susana Muñoz"}]}],mostDownloadedChaptersLast30Days:[{id:"56612",title:"Reproduction in Goats",slug:"reproduction-in-goats",totalDownloads:2892,totalCrossrefCites:3,totalDimensionsCites:4,abstract:"Reproductive activity of the goat begins when the females reach puberty, which happens at 5 months of age. The ovarian or estrous cycle is the period between two consecutive estrus. It is also the time that lasts the development of the follicle in the ovary, until rupture occurs and ovulation takes place, which coincides with the appearance of estrus. This chapter will describe the physiological and endocrinological bases of estrus in the goat. Likewise, factors affecting the presence of estrus and ovulation will be described. At another point, synchronization of estrus and ovulation, factors affecting the presence of estrus and external symptoms of estrus, will be described. To achieve synchronization of estrus or induction of ovulation within or outside the breeding season, it may be necessary to manage light hours, male effect, and/or use of hormones. The importance of artificial insemination is described, as well as the current situation of this technique worldwide. Currently, the techniques of artificial insemination in goats have been limited worldwide, due to the lack of resources of producers and trained technicians. The techniques of artificial insemination with estrous synchronization programs and ovulation with current research results will be described.",book:{id:"5987",slug:"goat-science",title:"Goat Science",fullTitle:"Goat Science"},signatures:"Fernando Sánchez Dávila, Alejandro Sergio del Bosque González\nand Hugo Bernal Barragán",authors:[{id:"201830",title:"Dr.",name:"Fernando",middleName:"Sanchez",surname:"Davila",slug:"fernando-davila",fullName:"Fernando Davila"},{id:"206127",title:"Dr.",name:"Alejandro Sergio",middleName:null,surname:"Del Bosque-Gonzalez",slug:"alejandro-sergio-del-bosque-gonzalez",fullName:"Alejandro Sergio Del Bosque-Gonzalez"},{id:"206128",title:"Dr.",name:"Hugo",middleName:null,surname:"Bernal-Barragán",slug:"hugo-bernal-barragan",fullName:"Hugo Bernal-Barragán"}]},{id:"58095",title:"The Innovative Techniques in Animal Husbandry",slug:"the-innovative-techniques-in-animal-husbandry",totalDownloads:3766,totalCrossrefCites:4,totalDimensionsCites:8,abstract:"Technology is developing rapidly. In this development, the transfer of computer systems and software to the application has made an important contribution. Technologic instruments made farmers can work more comfortable and increased animal production efficiency and profitability. Therefore, technologic developments are the main research area for animal productivity and sustainability. Many technologic equipment and tools made animal husbandry easier and comfortable. Especially management decisions and applications are effected highly ratio with this rapid development. In animal husbandry management decisions that need to be done daily are configured according to the correctness of the decisions to be made. At this point, smart systems give many opportunities to farmers. Milking, feeding, environmental control, reproductive performance constitute everyday jobs most affected by correct management decisions. Human errors in this works and decisions made big effect on last product quality and profitability are not able to be risked. This chapter deal with valuable information on the latest challenges and key innovations affecting the animal husbandry. Also, innovative approaches and applications for animal husbandry are tried to be summarized with detail latest research results.",book:{id:"6384",slug:"animal-husbandry-and-nutrition",title:"Animal Husbandry and Nutrition",fullTitle:"Animal Husbandry and Nutrition"},signatures:"Serap Göncü and Cahit Güngör",authors:[{id:"215579",title:"Prof.",name:"Serap",middleName:null,surname:"Goncu",slug:"serap-goncu",fullName:"Serap Goncu"},{id:"218971",title:"Dr.",name:"Cahit",middleName:null,surname:"Güngör",slug:"cahit-gungor",fullName:"Cahit Güngör"}]},{id:"58486",title:"Quality of Chicken Meat",slug:"quality-of-chicken-meat",totalDownloads:3290,totalCrossrefCites:18,totalDimensionsCites:26,abstract:"Chicken meat is considered as an easily available source of high-quality protein and other nutrients that are necessary for proper body functioning. In order to meet the consumers’ growing demands for high-quality protein, the poultry industry focused on selection of fast-growing broilers, which reach a body mass of about 2.5 kg within 6-week-intensive fattening. Relatively low sales prices of chicken meat, in comparison to other types of meat, speak in favor of the increased chicken meat consumption. In addition, chicken meat is known by its nutritional quality, as it contains significant amount of high-quality and easily digestible protein and a low portion of saturated fat. Therefore, chicken meat is recommended for consumption by all age groups. The technological parameters of chicken meat quality are related to various factors (keeping conditions, feeding treatment, feed composition, transport, stress before slaughter, etc.). Composition of chicken meat can be influenced through modification of chicken feed composition (addition of different types of oils, vitamins, microelements and amino acids), to produce meat enriched with functional ingredients (n-3 PUFA, carnosine, selenium and vitamin E). By this way, chicken meat becomes a foodstuff with added value, which, in addition to high-quality nutritional composition, also contains ingredients that are beneficial to human health.",book:{id:"6384",slug:"animal-husbandry-and-nutrition",title:"Animal Husbandry and Nutrition",fullTitle:"Animal Husbandry and Nutrition"},signatures:"Gordana Kralik, Zlata Kralik, Manuela Grčević and Danica Hanžek",authors:[{id:"207236",title:"Dr.",name:"Gordana",middleName:null,surname:"Kralik",slug:"gordana-kralik",fullName:"Gordana Kralik"},{id:"227281",title:"Prof.",name:"Zlata",middleName:null,surname:"Kralik",slug:"zlata-kralik",fullName:"Zlata Kralik"},{id:"227283",title:"Dr.",name:"Manuela",middleName:null,surname:"Grčević",slug:"manuela-grcevic",fullName:"Manuela Grčević"},{id:"227284",title:"BSc.",name:"Danica",middleName:null,surname:"Hanžek",slug:"danica-hanzek",fullName:"Danica Hanžek"}]},{id:"56453",title:"Goat System Productions: Advantages and Disadvantages to the Animal, Environment and Farmer",slug:"goat-system-productions-advantages-and-disadvantages-to-the-animal-environment-and-farmer",totalDownloads:4328,totalCrossrefCites:5,totalDimensionsCites:21,abstract:"Goats have always been considered very useful animals. Goats success is related to its excellent adaptability to the difficult mountain conditions, extreme weather and low value feed acceptance, versatile habits and high production considering their size. These are some reasons because goats are among the first animals to be domesticated. In terms of evolution, goats could be separated by their dispersion area in three large groups: the European, the Asian, and the African. Global goat populations, mainly in Africa and in Asia, have increased for centuries but very strongly in the past decades, well above the world population growth. They are also used for forest grazing, an integrated and alternative production system, very useful to control weed growth reducing fire risk. Despite some exceptions, no large‐scale effort to professionalize this industry has been made so far. There are consumers for goat dairy products and there is enough global production, but misses a professional network between both. Regarding goat meat, the world leadership also stays in Africa and Asia, namely in China, and there is a new phenomenon, the spreading of goat meat tradition through Europe due to migrants from Africa and other places with strong goat meat consumption.",book:{id:"5987",slug:"goat-science",title:"Goat Science",fullTitle:"Goat Science"},signatures:"António Monteiro, José Manuel Costa and Maria João Lima",authors:[{id:"190314",title:"Prof.",name:"António",middleName:"Cardoso",surname:"Monteiro",slug:"antonio-monteiro",fullName:"António Monteiro"},{id:"203680",title:"Prof.",name:"Maria João",middleName:null,surname:"Lima",slug:"maria-joao-lima",fullName:"Maria João Lima"},{id:"203683",title:"MSc.",name:"José Manuel",middleName:null,surname:"Costa",slug:"jose-manuel-costa",fullName:"José Manuel Costa"}]},{id:"70760",title:"Induction and Synchronization of Estrus",slug:"induction-and-synchronization-of-estrus",totalDownloads:1716,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"Estrus cycle is a rhythmic change that occur in the reproductive system of females starting from one estrus phase to another. The normal duration of estrus cycle is 21 days in cow, sow, and mare, 17 days in ewe, and 20 days in doe. The species which exhibit a single estrus cycle are known as monstrous and species which come into estrus twice or more are termed polyestrous animals. Among them some species have estrus cycles in a particular season and defined as seasonal polyestrous. It includes goats, sheep, and horses. On the other hand, cattle undergo estrus throughout the year. The estrus inducers can grossly be divided into two parts, that is, non-hormonal and hormonal. Non-hormonal treatments include plant-derived heat inducers, mineral supplementation, uterine and ovarian massage, and use of Lugol’s iodine. The hormones that are used in estrus induction are estrogen, progesterone, GnRH, prostaglandin, insulin, and anti-prolactin-based treatment. Synchronization can shorten the breeding period to less than 5 days, instead of females being bred over a 21-day period, depending on the treatment regimen. The combination of GnRH with the prostaglandin F2α (PGF2α)- and progesterone-based synchronization program has shown a novel direction in the estrus synchronization of cattle with the follicular development manipulation.",book:{id:"8545",slug:"animal-reproduction-in-veterinary-medicine",title:"Animal Reproduction in Veterinary Medicine",fullTitle:"Animal Reproduction in Veterinary Medicine"},signatures:"Prasanna Pal and Mohammad Rayees Dar",authors:[{id:"299126",title:"Dr.",name:"Mohammad Rayees",middleName:null,surname:"Dar",slug:"mohammad-rayees-dar",fullName:"Mohammad Rayees Dar"},{id:"311663",title:"Dr.",name:"Prasanna",middleName:null,surname:"Pal",slug:"prasanna-pal",fullName:"Prasanna Pal"}]}],onlineFirstChaptersFilter:{topicId:"25",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"82457",title:"Canine Hearing Management",slug:"canine-hearing-management",totalDownloads:3,totalDimensionsCites:0,doi:"10.5772/intechopen.105515",abstract:"The United States military employs multipurpose canines as force multipliers. A newly developed baseline audiology program applicable to noise effects on the hearing threshold for these dogs has just been developed by the University of Cincinnati FETCHLAB using brainstem auditory evoked potentials to detect estimated threshold shifts in this population. Dogs that are routinely deployed are subject to consistent exposure to noise in the field. Few investigations have focused on the effects of transport noise on the auditory system in multipurpose dogs. The consequence of these dogs having a significant hearing threshold shift is a failure of the dog to properly respond to voice commands and to miss critical acoustic cues while on target. This chapter specifically discusses the baseline protocol for audiological testing of special operations’ multipurpose canines related to helicopter transport.",book:{id:"11580",title:"Recent Advances in Canine Medicine",coverURL:"https://cdn.intechopen.com/books/images_new/11580.jpg"},signatures:"Peter M. Skip Scheifele, Devan Marshall, Stephen Lee, Paul Reid, Thomas McCreery and David Byrne"},{id:"82285",title:"Parvovirus Vectors: The Future of Gene Therapy",slug:"parvovirus-vectors-the-future-of-gene-therapy",totalDownloads:6,totalDimensionsCites:0,doi:"10.5772/intechopen.105085",abstract:"The unique diversity of parvoviral vectors with innate antioncogenic properties, autonomous replication, ease of recombinant vector production and stable transgene expression in target cells makes them an attractive choice as viral vectors for gene therapy protocols. Amongst various parvoviruses that have been identified so far, recombinant vectors originating from adeno-associated virus, minute virus of mice (MVM), LuIII and parvovirus H1 have shown promising results in many preclinical models of human diseases including cancer. The adeno-associated virus (AAV), a non-pathogenic human parvovirus, has gained attention as a potentially useful vector. The improved understanding of the metabolism of vector genomes and the mechanism of transduction by AAV vectors is leading to advancement in the development of more sophisticated AAV vectors. The in-depth studies of AAV vector biology is opening avenues for more robust design of AAV vectors that have potentially increased transduction efficiency, increased specificity in cellular targeting, and an increased payload capacity. This chapter gives an overview of the application of autonomous parvoviral vectors and AAV vectors, based on our current understanding of viral biology and the state of the platform.",book:{id:"11580",title:"Recent Advances in Canine Medicine",coverURL:"https://cdn.intechopen.com/books/images_new/11580.jpg"},signatures:"Megha Gupta"},{id:"81793",title:"Canine parvovirus-2: An Emerging Threat to Young Pets",slug:"canine-parvovirus-2-an-emerging-threat-to-young-pets",totalDownloads:19,totalDimensionsCites:0,doi:"10.5772/intechopen.104846",abstract:"Canine parvovirus-2 (CPV-2) is a highly contagious and key enteropathogen affecting the canine population around the globe by causing canine parvoviral enteritis (CPVE) and vomition. CPVE is one of the the leading causes of morbidity and mortality in puppies and young dogs. Over the years, five distinct antigenic variants of CPV-2, namely CPV-2a, CPV-2b, new CPV-2a, new CPV-2b, and CPV-2c, have emerged throughout the world. CPV-2 infects a diverse range of wild animals, and the newer variants of CPV-2 have expanded their host range to include felines. Despite the availability of highly specific diagnostics and efficacious vaccines, CPV-2 outbreaks have been reported globally due to the emergence of newer antigenic variants, expansion of the viral host range, and vaccination failures. The present chapter describes the latest information pertaining to virus properties and replication, disease manifestations in animals, and an additional recent updates on diagnostic, prevention and control strategies of CPV-2.",book:{id:"11580",title:"Recent Advances in Canine Medicine",coverURL:"https://cdn.intechopen.com/books/images_new/11580.jpg"},signatures:"Mithilesh Singh, Rajendran Manikandan, Ujjwal Kumar De, Vishal Chander, Babul Rudra Paul, Saravanan Ramakrishnan and Darshini Maramreddy"},{id:"81271",title:"The Diversity of Parvovirus Telomeres",slug:"the-diversity-of-parvovirus-telomeres",totalDownloads:38,totalDimensionsCites:0,doi:"10.5772/intechopen.102684",abstract:"Parvoviridae are small viruses composed of a 4–6 kb linear single-stranded DNA protected by an icosahedral capsid. The viral genes coding non-structural (NS), capsid, and accessory proteins are flanked by intriguing sequences, namely the telomeres. Telomeres are essential for parvovirus genome replication, encapsidation, and integration. Similar (homotelomeric) or different (heterotelomeric) at the two ends, they all contain imperfect palindromes that fold into hairpin structures. Up to 550 nucleotides in length, they harbor a wide variety of motifs and structures known to be recognized by host cell factors. Our study aims to comprehensively analyze parvovirus ends to better understand the role of these particular sequences in the virus life cycle. Forty Parvoviridae terminal repeats (TR) were publicly available in databases. The folding and specific DNA secondary structures, such as G4 and triplex, were systematically analyzed. A principal component analysis was carried out from the prediction data to determine variables signing parvovirus groups. A special focus will be put on adeno-associated virus (AAV) inverted terminal repeats (ITR), a member of the genus Dependoparvovirus used as vectors for gene therapy. This chapter highlights the diversity of the Parvoviridae telomeres regarding shape and secondary structures, providing information that could be relevant for virus-host interactions studies.",book:{id:"11580",title:"Recent Advances in Canine Medicine",coverURL:"https://cdn.intechopen.com/books/images_new/11580.jpg"},signatures:"Marianne Laugel, Emilie Lecomte, Eduard Ayuso, Oumeya Adjali, Mathieu Mével and Magalie Penaud-Budloo"},{id:"79209",title:"Virtual Physiology: A Tool for the 21st Century",slug:"virtual-physiology-a-tool-for-the-21st-century",totalDownloads:153,totalDimensionsCites:0,doi:"10.5772/intechopen.99671",abstract:"Veterinary physiology is a basic curricular unit for every course within the veterinary field. It is mandatory to understand how the animal body works, and what to expect of a healthy body, in order to recognize any misfunction, and to be able to treat it. Classic physiology teaching involves wet labs, much equipment, many reagents, some animals, and a lot of time. But times are changing. In the 21st century, it is expected that the teaching and learning process can be more active and attractive, motivating students to learn better. It is necessary to understand what students like, and to introduce novelties into the school routine. The use of a game-based learning, using “new” technologies, creating virtual experiences and labs, reducing the costs of reagents, equipment, and especially reducing the use of animals, will be the future for physiology teaching.",book:{id:"10665",title:"Updates on Veterinary Anatomy and Physiology",coverURL:"https://cdn.intechopen.com/books/images_new/10665.jpg"},signatures:"Carmen Nóbrega, Maria Aires Pereira, Catarina Coelho, Isabel Brás, Ana Cristina Mega, Carla Santos, Fernando Esteves, Rita Cruz, Ana I. Faustino-Rocha, Paula A. Oliveira, João Mesquita and Helena Vala"},{id:"78543",title:"Pulmonary Vein: Embryology, Anatomy, Function and Disease",slug:"pulmonary-vein-embryology-anatomy-function-and-disease",totalDownloads:183,totalDimensionsCites:0,doi:"10.5772/intechopen.100051",abstract:"Four pulmonary veins come from respective lung lobes drain oxygen-rich blood back to the left atrium. Failure of incorporation with the left atrium can lead to a condition, called Cor triatriatum sinister, that the left atrium is separated into two chambers by an abortive fibrous tissue. The venous system of lung and whole body communicate with each other in the earlier time and they will be disconnected in the following developmental process. Total or partial anomalous pulmonary venous connection refers to that there is/are some degree of the communication exists after birth, which can occur in different sites. In the veterinary field, retrospective studies and several case reports have been published to describe these rare congenital cardiovascular diseases in several species. More cases are need for better understanding their clinical manifestation, treatment options and outcomes.",book:{id:"10665",title:"Updates on Veterinary Anatomy and Physiology",coverURL:"https://cdn.intechopen.com/books/images_new/10665.jpg"},signatures:"Chan I-Ping and Hsueh Tung"}],onlineFirstChaptersTotal:13},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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She has been a faculty member at the University of California, Riverside in the School of Education since 2016. Her research focuses on translational studies to explore the reward system in ASD, as well as how anxiety contributes to social challenges in ASD. She also investigates how behavioral interventions affect neural activity, behavior, and school performance in children with ASD. She is also involved in the diagnosis of children with ASD and is a licensed clinical psychologist in California. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. 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Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. He is also Associate Editor of Biotech.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. She is an author of about 90 publications (According to Scopus: H-Index: 23; According to WOS: H-Index: 20) on peer-reviewed journals, a member of the “Società Italiana di Biochimica e Biologia Molecolare,“ and a Consultant Reviewer for International Journal of Molecular Science, Journal of Chromatography A, COPD, Plos ONE and Nutritional Neuroscience.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,series:{id:"11",title:"Biochemistry"}}},seriesLanding:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"June 29th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:318,numberOfPublishedBooks:32,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},subseries:[{id:"14",title:"Cell and Molecular Biology",keywords:"Omics (Transcriptomics; Proteomics; Metabolomics), Molecular Biology, Cell Biology, Signal Transduction and Regulation, Cell Growth and Differentiation, Apoptosis, Necroptosis, Ferroptosis, Autophagy, Cell Cycle, Macromolecules and Complexes, Gene Expression",scope:"The Cell and Molecular Biology topic within the IntechOpen Biochemistry Series aims to rapidly publish contributions on all aspects of cell and molecular biology, including aspects related to biochemical and genetic research (not only in humans but all living beings). We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",annualVolume:11410,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",fullName:"Abdulsamed Kükürt",profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",institutionString:null,institution:{name:"Kafkas University",institutionURL:null,country:{name:"Turkey"}}},{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/83566",hash:"",query:{},params:{id:"83566"},fullPath:"/profiles/83566",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()