Computational tools in the study of the transcriptome.
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These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
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IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
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Rugescu",coverURL:"https://cdn.intechopen.com/books/images_new/894.jpg",editedByType:"Edited by",editors:[{id:"8615",title:"Prof.",name:"Radu",surname:"Rugescu",slug:"radu-rugescu",fullName:"Radu Rugescu"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},onlineFirst:{chapter:{type:"chapter",id:"69666",title:"Bioinformatics as a Tool for the Structural and Evolutionary Analysis of Proteins",doi:"10.5772/intechopen.89594",slug:"bioinformatics-as-a-tool-for-the-structural-and-evolutionary-analysis-of-proteins",body:'\nThe study to understand the functioning of the cell, as well as the molecules and processes that are carried out within it, originated the use of various disciplines and sciences to facilitate the progress in research for its characterization over time. In the 1950s, the sequencing of small biological molecules began, and in 1956, the sequencing of the first protein was achieved. Thus, Margaret O. Dyhoff determined that bovine insulin is a small peptide of 51 amino acids. With these advances and the constant production of biological information, there was a need to collect and organize all the information generated from these sequencing projects [1]. In 1965, the first biological sequence database was created, in which all the DNA and protein sequences described up to that time were stored and made available to the scientific community. Eight years later, the oldest known database was created, which is still in force today,
In the 80s, bioinformatics had already gained a new meaning in scientific research, so several research groups such as Theoretical Biology and Biophysics Group attached to the American Institute The Alamos National Laboratory, together with Stanford University, gave rise to the best-known database in the world called GenBank. Almost at the same time, in 1981, Temple Smith and Michael Waterman extensively reviewed the mathematical algorithms for comparing biological sequences. As a result of their analysis, they generated the well-known local alignment algorithm that allowed to optimize the comparison of biological sequences, being the most important contribution for the direct comparison of sequences and cornerstone of the alignment by sequence pair [3].
\nA few years after the creation of
The National Center for Biotechnology Information (NCBI) makes the following definition:
\nBioinformatics is a field of science in which various disciplines such as applied mathematics, statistics, artificial intelligence, chemistry, biochemistry, computing and information technology converge, whose objective is to facilitate the discovery of new biological ideas, as well as create global perspectives from which unifying principles in biology can be discerned [6].
\nIt consists of two complementary subfields with each other:
The development of computer tools and databases.
The application of these in the generation of biological knowledge to better understand living systems [7].
According to the
\n
\n
\n
\n
There are primary databases, which contain direct information on the sequence, structure or pattern of DNA or protein expression, and secondary, which contains data derived from primary databases, such as mutations, evolutionary relationships, grouping by families or by functions, involvement in diseases, etc.
\nA
Data mining is oriented towards the study of techniques to extract valuable information from a large amount of biological data. For this, efficient software tools are necessary to recover data, compare biological sequences, discover patterns and visualize the discovery of knowledge [8].
\nAmong the most common data mining techniques in bioinformatics can be highlighted [8]:
\n
\n
The areas in which bioinformatics is currently developed are many and varied, ranging from simple tasks such as direct acquisition of data from DNA or protein sequencing assays (when techniques such as mass spectrophotometry are used), until the development of software for the storage and analysis of the data, which implies in many cases, the generation of algorithms that require both mathematical and biological knowledge. Within the areas in which bioinformatics takes place are genomics, proteomics, pharmacogenetics and phylogeny. The plant genome databases and gene expression analysis of this profile have played an important role in the development of new crop varieties that have higher productivity and more disease resistance [7].
\nSpecifically, bioinformatics encompasses the development of databases or knowledge to store and retrieve biological data, algorithms to analyze and determine their relationships with biological data, and the statistical tools to identify and interpret data sets. The following describes in detail what refers to metabolomics, transcriptomics, proteomics, comparative genomics, functional genomics, phylogeny and protein modeling.
\nThe metabolomics was originally proposed as a tool of functional genomics, but its use has been extended much more, as it has had great advances like other omics sciences, such as transcriptomics and proteomics; because the metabolomic work is determined by physical-chemical characteristics of organic molecules unlike the genes, mRNA and proteins that come from a specific sequence, so the success of the characterization of these biopolymers is thanks to bioinformatics technology and tools that help sequence characterization [12]. Its objective is to detect, quantify and interpret the overall analysis of all metabolites; these studies are used in various areas and, like proteomics, one of its main contributions is biomarkers, helping to identify metabolites that are correlated with diseases and environmental exposures [13]. Metabolites are chemical entities that do not come from a transfer of information within the cell, coupled with this, they are also characterized by being diverse as they are substrates and metabolism products that drive essential cellular functions, such as energy production and storage, signal transduction and cell apoptosis; in this great diversity of chemical structures we find endogenous and exogenous metabolites, the former are produced naturally by an organism and the latter come from interaction with the outside. The great diversity of molecules reflects in a wide range of polarities, molecular weights, functional groups, stability and chemical reactivity, etc. [12, 13].
\nAmong the first reports of metabolite detection are those where mass spectrometry (MS) was used to separate a wide range of metabolites present in urine and tissue extracts [14]. In addition, multicomponent analyzes were described to obtain the metabolic profile for three types of urinary constituents: steroids, acids, drugs and drug metabolism [15]. On the other hand, there are reports where physical, chemical or psychological changes can cause biological responses such as oxidative stress and inflammation; among the biomarkers that are the result of a chemical reaction are lipoperoxides or oxidized proteins that are the result of the reaction of molecules with reactive oxygen species (ROS) and those that represent the biological response to stress, such as the transcription factor NRF2 or inflammation and inflammatory cytokines [16]. Among the best known and clinically used examples we find glucose as a marker of diabetes [17] and phenylalanine as a marker of congenital metabolic disorder [18].
\nBecause metabolites play important roles in the biological pathways; its differential flow or regulation can reveal new knowledge about diseases and environmental influences, so one of the most important objectives of the metabolic analysis has been to assign the identity of the metabolite within a metabolic pathway [19, 20]; generating a large amount of data; requiring for its processing an arduous mathematical, statistical and bioinformatic work [12, 21, 22], this last area is crucial for the development of metabolomics as it helps in the handling of data and information, analytical data processing, metabolomic standards, ontology, statistical analysis, mining and data integration, and mathematical modeling of metabolomic networks with antecedents of biological systems [12], it is also necessary to decide which metabolites are biologically more significant. This can be achieved by helping the identification process, reducing the redundancy of characteristics, presenting better candidates for the MS, accelerating or automating the workflow, recovering data through characteristics through meta-analysis or multigroup analysis, or using stable isotopes and mapping of pathways. For all the above, in recent years, the technologies for analyzing metabolites have undergone improvements, establishing more efficient protocols for experimental design, as well as better sample extraction techniques and data acquisition that have been worthwhile in providing sets of complex and solid data [20].
\nThe database management system for metabolomics requires the collection of raw and processed metadata, some important aspects for comparing data and obtaining results in different laboratories and reproducing experimental conditions are: The nature and treatment of samples prior to study. Among the bases and tools for the analysis and visualization of available data are: Kyoto Encyclopedia of Genes and Genomes (KEGG; http://www.genome.ad.jp/kegg/) [23] and Metabolic Pathways From all Domains of Life (MetaCyc; http://metacyc.org/) [24].
\nThe genes response to intracellular or extracellular stimuli includes a hierarchy of signals that allows genes encoded in the DNA to be expressed or repressed by the transcription process. The total set of transcripts (RNA molecules) produced by a cell under a given condition and time, is defined as a
The RNA study approach has changed from the sequencing of the first determined RNA molecule, to the sequencing of the transcriptome using new generation technologies [25].
The growing importance of DNA sequencing in model organisms, as well as in the quest to understand the dogma of biology, the NGS technologies (Next Generation Sequencing) arise, which have high yields in the treatment of the sample, are reproducible and highly reliable, as well as accessible and economical, to the point of being more profitable than sequencing by SANGER. These next-generation technologies are based on sequencing by synthesis (SBS) known as pyrosequencing, the transcriptomic variant of pyrosequencing technology is known as short-reading massive parallel sequencing (RNA-seq). The availability of this technology has revolutionized the approach of transcriptome study, having commercially available Roche/454; Applied Biosystems SOLID; HeliScope e Illumina [36].
\nFrom the first RNA studies based on sequencing by SANGER to NGS technologies, bioinformatics has been a key tool in the analysis process. Initially the differential expression based on the analysis by Microarrays presented its own computational challenges [36], currently while the reads are shorter than those created by sequencing by SANGER, NGS has a higher performance and generates data set of up to 50 gigabases per run [37], this requires algorithms capable of processing this amount of data in the shortest time possible and with a high degree of reliability.
\nThe study of the transcriptome by RNAseq involves different stages ranging from RNA extraction, library construction, sequencing and data analysis. In this last step four main stages are distinguished (a)
Process | \nTools | \nObjective | \nReferences | \n
---|---|---|---|
Quality analysis of reads | \nFastQC Fastx-toolkit Trimmomatic, PRINSEq, Flexbar | \nIt analyzes the quality of the reads It debugs poor quality reads | \n[38, 39, 40, 41, 42] | \n
Assembly | \nTrinity, Trans-ABySS, Oases, IDBA-Tran TOPHAT, STAR, IDBA-Tran, HISAT | \nAssembly of reads without genome or reference transcriptome Assembly of reads with genome or reference transcriptome | \n[46, 55, 56] [43, 44, 57, 58] | \n
Classification of transcripts | \nBLAST, BLAT, GMAT, AUGUSTUS CPAT, FEELnc, NRC, lncRScan-SVM | \nIt identifies coding transcripts by homology or by known transcript characteristics | \n[5, 59, 60, 61] [62, 63, 64, 65] | \n
Mapping | \nTOPHAT, STAR, HISAT, HISAT2, Bowtie | \nIt aligns reads with a reference genome or transcriptome | \n[43, 44, 58, 66] | \n
Quantification | \nRSEM, Feature Count StringTie, Salmon, Kallisto | \nIt estimates the number of transcripts with or without their alignment | \n[45, 49, 67, 68, 69] | \n
Classification of coding and non-coding transcripts | \nBEDTools, glbase | \nIt determines the coordinates of the reference genome | \n[70] | \n
BLAST, BLAT, GMAP, AUGUSTUS | \nThrough homology it manages to determine known sequences of transcripts found in databases | \n[5, 59, 60, 61] | \n|
CPAT, FELLnc, lncRScan-SVM, NRC | \nIt evaluates characteristics of coding and non-coding transcripts | \n[62, 63, 64, 65] | \n|
Small RNA analysis | \nmiRDeep Pic Tar | \nIt quantifies known micro RNAs and identify new RNAs | \n[71, 72, 73] | \n
PiPMir | \nIt identifies new micros RNAs in plants | \n[74] | \n|
DARIO | \nIt allows the recognition of micro RNAs, snoRNA and tRNA | \n[73] | \n|
IntaRNA | \nIt analyzes micro RNAs in eukaryotes and small bacterial RNAs | \n[75, 76] | \n|
CopraRNA | \nIt makes comparative predictions that include functional enrichment analysis | \n[76, 77] | \n
Computational tools in the study of the transcriptome.
The identification of non-coding RNAs and small RNAs is a vital issue in genetic analysis [29], in this sense algorithms have been developed for the analysis of this type of RNAs in particular (Table 1). Currently, the tools used to classify coding and non-coding sequences have two aspects, those that classify transcripts according to similarity and those that use known coding and non-coding properties [47]. Similarity-based tools classify transcripts, taking as reference the amino acid sequences of their transcripts translated with known protein coding genes, for example BLAST [5], BLATS [59], GMAP [60]. On the other hand, tools focused on coding and non-coding characteristics are based on the properties of known transcripts to predict whether a transcript encodes or not for a protein. The coding potential can be estimated using automatic learning approaches such as CPAT [62], FEELnc [63], lncRScan-SVM [64] and NRC [65]. These exclude transcripts based on properties such as transcription length, length of open reading frame (ORF), ORF coverage, k-mer frequency, codon usage bias, in addition to being optimized for different techniques [47]. In the choice of the tool to be used to evaluate the coding potential of a transcript, it will depend on what is sought in the study, if there is a good annotation and reference genome the tools based on similarity are practical and feasible in the analysis. However, in organisms that lack good gene annotations it is advisable to use tools based on coding and non-coding characteristics, which also allow to identify new genes. On the other hand, the availability of small readings opened a new field of study for small RNAs such as microRNAs (miRNAs), small RNAs of interference (siRNA) and piwiRNAs (piRNAs); Currently there are specialized tools for this type of RNA that provide additional biological knowledge. In this case miRDeep and its varieties are widely used to quantify known and novel RNA (miRNA), from the sequencing of small RNA by RNAseq [71, 72]; PiPMir [74] has been used for the detection of miRNA in plants. DARIO (http://dario.bioinf.uni-leipzig.de/index.py) is a web service that allows not only the recognition of new microRNAs but also small RNAs derived from other types of parental RNAs, such as snoRNA and tRNA [73]. Pic Tar is an algorithm for the identification of micro RNAs, which is based on functional interactions of micro RNA [78, 79]. IntaRNA has been designed for the study of micro RNAs in eukaryotes and small bacterial RNAs (RNAs) [75, 76]. CopraRNA is a comparative prediction algorithm that is complemented by post-processing methods that includes functional enrichment analysis [76, 77]. Finally, after analyzing the data, the biological conclusions must be carefully interpreted.
\nTranscriptome sequences provide resources for gene expression profile studies, as well as for the identification of mutations, sequence aberrations and RNA editing events [25], the above is possible to the existence of the open reading frame (ORF), however, in genomic data this does not imply the existence of a functional gene; despite the great advances in bioinformatics that facilitate the analysis and prediction of genes with the help of comparative genomics, and although they are years of development of molecular simulation methods, attempts to improve models that are already relatively close to the structure native, they have had little success, which may be due to inaccuracies in the potential functions used in simulations, such as the treatment of electrostatic and solvation effects or it may be necessary to improve sampling strategies due to the relatively long folding time scale of proteins; the combination of chemistry and physics with the large amount of information in known protein structures could provide a better route for the development of enhanced potential functions. Currently, it is difficult to accurately predict protein structures from genes, the success rate for the correct prediction of structures remains low [25, 80, 81]. Proteomics involves various technologies for deep proteome analysis, thus achieving quantification and identification of these proteins; covering the part of functional analysis of genetic products, interaction studies, and protein localization, which helps explain the identity of an organism’s proteins to know the structure and function. However, considering that the proteome is highly dynamic due to the complex regulatory systems that control the levels of protein expression, its use is limited, since in addition to the use of specialized personnel, facilities and equipment, software is also included for equipment, and databases, which increases costs [80, 82, 83]. Proteomics is constantly updated, generating challenges ranging from sample preparation to data collection. A large amount of information is generated from protein folding models, three-dimensional structures, prediction of unknown protein structures and functions, data obtained from the separation of proteins by electrophoresis in two-dimensional gels, isoelectric focusing, 2D protein visualization, peptide mass fingerprinting (PMF), MS, MS in tandem, etc., the above generates high performance proteomes with the help of bioinformatics, which introduces new algorithms to handle a large amount of heterogeneous data [84, 85, 86].
\nSome of the most used platforms in proteomics are: The Basic Local Alignment Search Tool (BLAST), Expert Protein Analysis System (ExPASy) and Protein Data Bank (PDB); BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi). It is one of the most used and updated platforms, which uses simple but powerful methods for protein analysis comparing amino acid sequences, which makes it possible to determine homology between proteins, where the algorithms used to perform this procedure guarantee the best possible alignment, however, it does not guarantee the best structure [5, 86, 87, 88, 89, 90]. ExPASy gives access to a wide variety of databases and analytical tools dedicated to proteins and proteomics. On the other hand, PDB (https://www.wwpdb.org/) is the global repository of three-dimensional structures of macromolecules that is updated weekly and contains more than 153,000 protein structures, resulting from crystallographic studies, X-rays or nuclear magnetic resonance (NMR) created by modeling software, all these platforms contain various servers that help classify proteins according to their sequence, structure and function [86, 91, 92].
\nAll this information is of great help, since it is used in different research areas, such as detection of diagnostic markers, candidates for vaccine production, understanding the mechanisms of pathogenicity, alteration of expression patterns in response to different signals and interpretation of functional protein pathways in different diseases [93, 94, 95, 96, 97, 98].
\nComparative genomics is a broad field of study that identifies differences between genomes and elucidates which of them are responsible for phenotypic changes in organisms [99]. In contrast to ‘traditional’ genomic studies that focus on a single genome per study [100], comparative genomics provides additional detailed information to that obtained from the analysis of a single genome, which can reveal the encoded functional potential of an organism compared to another [101, 102, 103]. Comparisons between different genomes of organisms lead to more rapid identification of different underlying mechanisms are shared between organisms and others that are different among them [104, 105, 106]. Likewise, comparative genomics allows a better understanding of how species have evolved [107]. In this sense, the concept of pangenome (Figure 1) refers to the set of genes in a particular species [106]. The commonly used partition of a pangenome considers three main parts: the central genome, the expendable or accessory genome and the singleton genome [108]. The central genes are responsible for the basic aspects of the biology of the species and its main phenotypic features; while accessory genes and singletons generally belong to supplementary biochemical pathways and functions that can confer selective advantages such as ecological adaptation [108]. While the global analysis of gene content (as in pangenome studies) provides information on differences in functional potential and possible phenotypic differences between organisms, specific central gene analyzes have also been used for studies of phylogenetic diversity [99, 108].
\nPangenome diagram of three different genomes.
Initially, the concept of pangenome was used to refer to bacterial genomes, however, over time it has been used to refer to genomes of eukaryotic organisms such as yeasts [106, 109], plants [108, 110, 111], and viruses [108, 112]. Different organisms can be compared despite their phenotypic differences and with respect to their relationship of kinship (phylogenetic distances) [105, 113]. The assembly of genomes from sequencing data by Illumina or PacBio methods [114] involves five important stages, these steps are described in Figure 2, as well as some of the tools used [106].
\nWorkflow for the de novo genome comparative analysis.
For gene comparisons databases with different characteristics are used, for example, to obtain gene families and identify their orthology the EDGAR database [108, 115] is used, as well as, the prokaryotic-genome analysis tool (PGAT) for the analysis of bacterial genomes [108, 116]. There are independent applications such as the Pan-genome analysis pipeline (PGAP) that have specific modules to perform the functional analysis of genes, the analysis and determination of each of the components of the pangenome, the detection of genetic variation as well as the analysis of Species evolution [108, 117], PanFunPro is a tool that allows pangenome analysis in protein prediction from genetic information [96]. There are tools that allow you to work with large amounts of data such as PanGP [118] and the large acale BSR [119].
\nThe bacterial pan genome analysis tool (BPGA) [120] is a recently published package for pangenome analysis with seven functional modules; In addition to routine analysis, it presents a series of novel features for subsequent analyzes such as phylogeny, as well as tools that allow determining the presence and absence of certain genes in specific strains, another module to perform subset analysis, content analysis atypical G+C and KEGG & COG mapping of central, accessory and unique genes [108, 121, 122, 123, 124].
\nFunctional genomics studies and assigns functions to the genome of an organism, including genes and non-genetic elements [125, 126], with the support of molecular and cellular biology studies, focused on the dynamic aspects of transcriptomics, proteomics and metabolomics [127], that allow to know the relationship of genes, their transcription, translation and protein-protein interactions [128, 129], that promote the phenotypic characteristics of each organism [125, 126]. A functional genomic approach can use multiple techniques for data analysis in a single study [129]. Apart from the tools of transcriptomics and proteomics, functional genomics needs of studies that allow us to know gene interactions [130, 131], genetic variations (polymorphisms) in different individuals through the study of SNPs [126, 132]. Likewise, it is important to know the regulation of genes in the expression of proteins that first carries out the analysis of promoter sequences, followed by the expression of the promoters and subsequently the expression of proteins [126, 133, 134]. Another study used for a rapid and systematic analysis of the expression of a large number of genes is the microarrays, which make it easier to observe the differential expression of genes from DNA or cDNA, as well as, allowing the finding gene functions novel and unexpected [135]. In addition, compare the pattern of gene expression under different conditions [136]. SAGE serial analysis of gene expression based on the study of cDNA allows to examine gene expression in a cell [126]. To perform a functional genomic observation, an assembled and identified genome must be had, which does not contain gaps, to avoid erroneous annotations. Subsequently, the assembled genome is compared with a reference genome, which together allows to predict genes. Next, the mapped elements are combined, and the biological information that allows to define an optimal set of annotations or functions is assigned. At the end, the data will have to be validated, this is achieved through manual inspections, experimental checks and quality measures [137]. To perform the genome annotation there are computational tools, one of the most used and friendly is Blast2GO which is a bioinformatics platform for high quality functional annotations and analysis of genomic data sets [138]. The data obtained can be shared with the public through databases so that other researchers can access them. Currently, GEO of NCBI is the public functional genomics database that provides tools that help users in the consultation and download of data [139]. Likewise, KEGG is a database that is used as a tool to understand the high-level functions and utilities of the biological system, such as the cell, the organism or the ecosystem, based on molecular level information, generated by sequencing of the genome and other high performance [140]. There are also databases that store specific information on each of the most important model organisms (Table 2).
\nReference organisms | \nDatabases | \nReferences | \n
---|---|---|
\n | \n\nhttps://www.genome.jp/kegg-bin/show_organism?org=eco\n | \n[141] | \n
\n | \n\nhttps://www.yeastgenome.org/\n | \n[142] | \n
\n | \n\nhttps://www.arabidopsis.org/\n | \n[143] | \n
\n | \n\nhttps://wormbase.org/#012-34-5\n | \n[144] | \n
\n | \n\nhttp://www.flybase.org/\n | \n[145] | \n
\n | \n\nhttp://zfin.org/\n | \n[146] | \n
\n | \n\nhttp://www.informatics.jax.org/\n | \n[147] | \n
\n | \n\nhttps://www.genome.jp/kegg-bin/show_organism?org=hsa\n | \n[148] | \n
Databases of reference organisms used for genomic analysis.
The sequencing of the genome of an organism, has allowed to know the set of all its genes, elucidating the functions and products that they express, as well as the mechanisms of regulation in different metabolic processes, where endless proteins participate. To determine their possible functions, biochemical and genetic analyzes are used in a classical way, however, sequencing has contributed to the knowledge about the type of amino acids that make it up, and through the use of software multiple sequences have been aligned, where they have those that have been fully characterized as well as proteins where their biochemical characteristics are unknown and by homology between amino acids can be inferred in the functions that these proteins can present [149]. The use of bioinformatics, in protein analysis is a challenge, in recent years, phylogenetic profiles have been fundamental to relate homologous proteins by aligning their sequences, where it has been revealed that many share highly conserved regions and similar structures [150]. Phylogeny analyzes the changes that occur within the sequences and groups them in a diagram with ramifications, called a phylogenetic tree, all those sequences that belong to the same family can be grouped into a clade and in turn into subfamilies, providing data on their evolution and functional diversity [151].
\nEukaryotic cells during their evolution have captured microorganisms that originated mitochondria, chloroplasts and other organelles, where their genes have been transferred to the nuclear genome, allowing the transport of encoded proteins in the nucleus. The different locations of proteins in the cell, and the different proteins that participate in cellular processes, have originated phylogenetic analyzes on the location of proteins in the cell, finding that they are closely related to prokaryotic proteins that have eukaryotes. The proteins of chloroplasts and mitochondria have a composition of amino acids, length, sequences and conserved regions very similar to those of prokaryotes [152, 153]. One of the limitations to analyze proteins among related organisms is that genomes must be complete, in order to determine the presence or absence of genes in these species [154].
\nThe high number of sequences that are stored in the different databases, have allowed to infer in the evolutionary relationships of different proteins, which when presenting homology retain their function during long evolutionary times, however, homologous proteins can perform the same activity, but the substrates they use can come from different routes [155]. When organisms adapt to different environmental conditions they cause mutational changes in genome sequences, causing amino acid substitutions in enzymes, making them improve their efficiency and specificity, to maintain their catalytic function. Not all genes that code for proteins are susceptible to mutation, due to the presence of essential amino acids in function, stability and folding, and therefore a restriction is generated. Many of the mutations are usually random and, in those proteins, where these changes have been observed, it is due to an evolutionary pressure. If the protein plays an important role in the functions of the organism and the mutation brings improvements in activity, the change in the genome is maintained and optimized, favored by selective pressure, otherwise, when the function of the protein is not relevant. In the cell, the mutant gene is removed from the genome by random deletions. Evolutionary mechanisms have given rise to homologous protein families, which share a common ancestor [155]. The study of ancestral enzymes has suggested that these presented a high thermostability, due to the Precambrian era that was thermophilic, in addition to the fact that most microorganisms and other organisms adapted to these environments with high temperatures. The ancestral protein alignments with the current ones show evidence of a slow evolution in structure, but not in amino acids [156]. Therefore, enzymes are the product of years of evolution, where they have undergone changes to obtain a specific function, as well as greater affinity with the substrate and/or act on multisubstrates. Therefore, the genetic variability has generated homologous genes (they descend from a common ancestor and are called orthologs) that encode adapted proteins to perform their catalysis in extreme conditions. However, there are also paralogous genes, which have diverged, to encode proteins with different activities [157], many times a particular characteristic is preserved, such as the binding of a molecule or reaction mechanism, but they specialize in carrying out the same reaction but on different substrates, different regulation mechanisms, as well as cell localization. On the other hand, orthologous proteins tend to have the same function and their sequences have a high conservation [155].
\nTo analyze these changes in the sequences, bioinformatics programs use algorithms and mathematical models, based on empirical matrices of amino acid substitution, as well as those that incorporate structural properties of the native state, such as secondary structure and accessibility [158]. Protein phylogeny studies are currently necessary to know protein-protein interactions in biological systems. Molecular or structural analyzes on proteins will require more information to respond if a protein is present in one or several species, as well as to predict the common ancestor and evolution times [159]. There are different methods to estimate the genetic distance of proteins, among the most used are the minimum distance, which predicts the phylogenetic relationship minimizing the total distance of the pairs of sequences adjacent nodes tree. While those of maximum parsimony and maximum likelihood, use the multiple sequence alignment, however, the maximum parsimony maximum builds a tree minimizing the total evolutionary changes between adjacent proteins and the maximum likelihood tries to minimize the probability of making such changes. The bioinformatics tools that use these algorithms are: TOPAL, Hennig86 and PAML, the computational packages that allow to occupy any of these are PHYLIP and PAUP, as well as MOLPHY, PASSML, PUZZLE, TAAR [160].
\nOne of the challenges of protein engineering and biology is to improve industrial processes, to achieve this it is necessary to determine the tertiary structure of proteins from the amino acid sequence, in order to design new proteins and even new medicines. Many of the protein structures that we know today have been obtained through experimentation by X-ray crystallography, NMR spectroscopy or cryo-EM, however, the large amount of proteins, makes these processes require more time and increase costs [161]. Modeling through bioinformatics programs has managed to predict the atomic structure of several proteins from their amino acid sequence, by comparison with known protein structures, commonly called templates, although these do not present an accuracy with traditional techniques, the processes are faster and more economical in addition to providing low resolution data during sequence comparison [162, 163]. If the protein studied presents a homolog of known structure, the analysis is easier and the generated model is of higher resolution, but if the homologs do not exist or are not identified, the modeling is constructed from scratch [164]. De novo modeling is based on the assembly of proteins using short peptide fragments, originating from known proteins based on similarity, although advances have been made using this process, it has only worked on proteins that contain less than 100 amino acids, on large proteins size is difficult to analyze due to lack of information, as well as the type of software used [161, 165].
\nThe 3D protein structures provide data at the molecular level, functions and properties, among which are the study of the catalytic mechanism, design and improvement of ligands, union of macromolecules with proteins, functional relationships through structural similarity and identification of conserved residues [55]. The interest in finding new protein models is generating a large amount of data, which is being stored in different databases, including Protein Data Bank, where the coordinates of the experimentally obtained atoms are stored; until 2014 this base contained more than 80 million sequences and more than 100,000 experimentally obtained 3D structures [166, 167]. These data have allowed the classification of proteins in different hierarchical levels as family, superfamily and fold in relation to their structure and evolution. All those that are grouped into a family are evolutionarily related to high sequence similarity. It is suggested that the different families that maintain a structure and function, present a common ancestor and are grouped into superfamilies and the difference between these is due to the folds or secondary structure that they possess [160]. In the last decade, the predictions by computational models have revealed the structure and function of many proteins, but the advances have been in some cases slow and expensive, due to the programming methods used and the precision of these during modeling. Currently working on automated bioinformatics servers that will generate models with a high percentage of accuracy [168, 169]. One of the most used servers worldwide is SWIIS-MODEL, which was the first to model proteins through homology, and in recent years has been automated allowing complex modeling, as well as the introduction of the modeling engines ProMod3 and QMEAN [167, 170, 171]. Most modeling algorithms use the following steps: (1) Identification of related structures, (2) template choice, (3) target sequence alignment with templates, (4) molding construction, (5) model evaluation. However, one of the limitations during homology protein modeling is the choice of model proteins or templates as well as alignments against the problem sequences [172, 173]. When the similarity of the sequences between the problem protein and that of the databases is low, the relationship and alignment can be improved if structural information is included during the analysis [166]. Advances in biocomputing have allowed the generation of tools for modeling proteins that are more reliable and easier to use, reducing time and cost in the analysis. However, it is necessary to carry out experimentation to confirm that the prediction is correct, in addition to improving the efficiency of the techniques and with more known protein sequences and stored in the databases, therefore the different bioinformatics tools will play an important role in the postgenomic era [160].
\nBioinformatics has evolved with daily work, which has allowed us to know how the biological molecules of a cell interact for their proper functioning, in addition to predicting various biological phenomena. In the last decade, the omic sciences have generated a great amount of data increasing the knowledge of the biological functions so that in the future they are able to predict diseases or formulate drugs with greater efficiency, however it is still necessary, to have a higher percentage of sequenced genes of the different organisms, as well as protein sequences, that allow enriching the databases, and with this more precise mathematical models are generated, which will benefit the computer programs so that they are more efficient, reliable, easy to use, reducing time and cost in the analyzes. This discipline becomes an essential part of biological studies every day, so its expansion and growth will be infinite, due to the evolutionary changes that are taking place in the cells caused by the different environmental phenomena.
\nThe authors declare no conflict of interest.
This is a brief overview of the main steps involved in publishing with IntechOpen Compacts, Monographs and Edited Books. Once you submit your proposal you will be appointed a Author Service Manager who will be your single point of contact and lead you through all the described steps below.
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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. 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He previously worked as a post-doctoral fellow at the Ben-Gurion University of Negev, Israel; University of the Free State, South Africa; and Central University of Technology Bloemfontein, South Africa. He obtained his Ph.D. in Organic Chemistry from Nagaoka University of Technology, Japan. He has published more than seventy-four journal articles and attended several national and international conferences as speaker and chair. Dr. Kendrekar has received many international awards. He has several funded projects, namely, anti-malaria drug development, MRSA, and SARS-CoV-2 activity of curcumin and its formulations. He has filed four patents in collaboration with the University of Central Lancashire and Mayo Clinic Infectious Diseases. 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Dr. Adimule has attended, chaired, and presented papers at national and international conferences. He is a guest editor for Topics in Catalysis and other journals. He is also an editorial board member, life member, and associate member for many international societies and research institutions. His research interests include nanoelectronics, material chemistry, artificial intelligence, sensors and actuators, bio-nanomaterials, and medicinal chemistry.",institutionString:"Angadi Institute of Technology and Management",institution:null},{id:"284317",title:"Prof.",name:"Kantharaju",middleName:null,surname:"Kamanna",slug:"kantharaju-kamanna",fullName:"Kantharaju Kamanna",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/284317/images/21050_n.jpg",biography:"Prof. K. Kantharaju has received Bachelor of science (PCM), master of science (Organic Chemistry) and Doctor of Philosophy in Chemistry from Bangalore University. He worked as a Executive Research & Development @ Cadila Pharmaceuticals Ltd, Ahmedabad. He received DBT-postdoc fellow @ Molecular Biophysics Unit, Indian Institute of Science, Bangalore under the supervision of Prof. P. Balaram, later he moved to NIH-postdoc researcher at Drexel University College of Medicine, Philadelphia, USA, after his return from postdoc joined NITK-Surthakal as a Adhoc faculty at department of chemistry. Since from August 2013 working as a Associate Professor, and in 2016 promoted to Profeesor in the School of Basic Sciences: Department of Chemistry and having 20 years of teaching and research experiences.",institutionString:null,institution:{name:"Rani Channamma University, Belagavi",country:{name:"India"}}},{id:"158492",title:"Prof.",name:"Yusuf",middleName:null,surname:"Tutar",slug:"yusuf-tutar",fullName:"Yusuf Tutar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/158492/images/system/158492.jpeg",biography:"Prof. Dr. Yusuf Tutar conducts his research at the Hamidiye Faculty of Pharmacy, Department of Basic Pharmaceutical Sciences, Division of Biochemistry, University of Health Sciences, Turkey. He is also a faculty member in the Molecular Oncology Program. He obtained his MSc and Ph.D. at Oregon State University and Texas Tech University, respectively. He pursued his postdoctoral studies at Rutgers University Medical School and the National Institutes of Health (NIH/NIDDK), USA. His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. He is currently a professor at the Institute of Biomaterials and Bioengineering (IBB), Tokyo Medical and Dental University (TMDU). From 2010 to 2012, he was the dean of the Graduate School of Biomedical Science. Since 2012, he has served as the vice dean of the Graduate School of Medical and Dental Sciences. He has been the director of the IBB since 2020. Dr. Kagechika’s major research interests are the medicinal chemistry of retinoids, vitamins D/K, and nuclear receptors. He has developed various compounds including a drug for acute promyelocytic leukemia.",institutionString:"Tokyo Medical and Dental University",institution:{name:"Tokyo Medical and Dental University",country:{name:"Japan"}}},{id:"94311",title:"Prof.",name:"Martins",middleName:"Ochubiojo",surname:"Ochubiojo Emeje",slug:"martins-ochubiojo-emeje",fullName:"Martins Ochubiojo Emeje",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94311/images/system/94311.jpeg",biography:"Martins Emeje obtained a BPharm with distinction from Ahmadu Bello University, Nigeria, and an MPharm and Ph.D. from the University of Nigeria (UNN), where he received the best Ph.D. award and was enlisted as UNN’s “Face of Research.” He established the first nanomedicine center in Nigeria and was the pioneer head of the intellectual property and technology transfer as well as the technology innovation and support center. Prof. Emeje’s several international fellowships include the prestigious Raman fellowship. He has published more than 150 articles and patents. He is also the head of R&D at NIPRD and holds a visiting professor position at Nnamdi Azikiwe University, Nigeria. He has a postgraduate certificate in Project Management from Walden University, Minnesota, as well as a professional teaching certificate and a World Bank certification in Public Procurement. Prof. Emeje was a national chairman of academic pharmacists in Nigeria and the 2021 winner of the May & Baker Nigeria Plc–sponsored prize for professional service in research and innovation.",institutionString:"National Institute for Pharmaceutical Research and Development",institution:{name:"National Institute for Pharmaceutical Research and Development",country:{name:"Nigeria"}}},{id:"436430",title:"Associate Prof.",name:"Mesut",middleName:null,surname:"Işık",slug:"mesut-isik",fullName:"Mesut Işık",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/436430/images/19686_n.jpg",biography:null,institutionString:null,institution:{name:"Bilecik University",country:{name:"Turkey"}}},{id:"268659",title:"Ms.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/268659/images/8143_n.jpg",biography:"Dr. Zhan received his undergraduate and graduate training in the fields of preventive medicine and epidemiology and statistics at the West China University of Medical Sciences in China during 1989 to 1999. He received his post-doctoral training in oncology and cancer proteomics for two years at the Cancer Research Institute of Human Medical University in China. In 2001, he went to the University of Tennessee Health Science Center (UTHSC) in USA, where he was a post-doctoral researcher and focused on mass spectrometry and cancer proteomics. Then, he was appointed as an Assistant Professor of Neurology, UTHSC in 2005. He moved to the Cleveland Clinic in USA as a Project Scientist/Staff in 2006 where he focused on the studies of eye disease proteomics and biomarkers. He returned to UTHSC as an Assistant Professor of Neurology in the end of 2007, engaging in proteomics and biomarker studies of lung diseases and brain tumors, and initiating the studies of predictive, preventive, and personalized medicine (PPPM) in cancer. In 2010, he was promoted to Associate Professor of Neurology, UTHSC. Currently, he is a Professor at Xiangya Hospital of Central South University in China, Fellow of Royal Society of Medicine (FRSM), the European EPMA National Representative in China, Regular Member of American Association for the Advancement of Science (AAAS), European Cooperation of Science and Technology (e-COST) grant evaluator, Associate Editors of BMC Genomics, BMC Medical Genomics, EPMA Journal, and Frontiers in Endocrinology, Executive Editor-in-Chief of Med One. He has\npublished 116 peer-reviewed research articles, 16 book chapters, 2 books, and 2 US patents. His current main research interest focuses on the studies of cancer proteomics and biomarkers, and the use of modern omics techniques and systems biology for PPPM in cancer, and on the development and use of 2DE-LC/MS for the large-scale study of human proteoforms.",institutionString:null,institution:{name:"Xiangya Hospital Central South University",country:{name:"China"}}},{id:"40482",title:null,name:"Rizwan",middleName:null,surname:"Ahmad",slug:"rizwan-ahmad",fullName:"Rizwan Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/40482/images/system/40482.jpeg",biography:"Dr. Rizwan Ahmad is a University Professor and Coordinator, Quality and Development, College of Medicine, Imam Abdulrahman bin Faisal University, Saudi Arabia. Previously, he was Associate Professor of Human Function, Oman Medical College, Oman, and SBS University, Dehradun. Dr. Ahmad completed his education at Aligarh Muslim University, Aligarh. He has published several articles in peer-reviewed journals, chapters, and edited books. His area of specialization is free radical biochemistry and autoimmune diseases.",institutionString:"Imam Abdulrahman Bin Faisal University",institution:{name:"Imam Abdulrahman Bin Faisal University",country:{name:"Saudi Arabia"}}},{id:"41865",title:"Prof.",name:"Farid A.",middleName:null,surname:"Badria",slug:"farid-a.-badria",fullName:"Farid A. Badria",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/41865/images/system/41865.jpg",biography:"Farid A. Badria, Ph.D., is the recipient of several awards, including The World Academy of Sciences (TWAS) Prize for Public Understanding of Science; the World Intellectual Property Organization (WIPO) Gold Medal for best invention; Outstanding Arab Scholar, Kuwait; and the Khwarizmi International Award, Iran. He has 250 publications, 12 books, 20 patents, and several marketed pharmaceutical products to his credit. He continues to lead research projects on developing new therapies for liver, skin disorders, and cancer. Dr. Badria was listed among the world’s top 2% of scientists in medicinal and biomolecular chemistry in 2019 and 2020. He is a member of the Arab Development Fund, Kuwait; International Cell Research Organization–United Nations Educational, Scientific and Cultural Organization (ICRO–UNESCO), Chile; and UNESCO Biotechnology France",institutionString:"Mansoura University",institution:{name:"Mansoura University",country:{name:"Egypt"}}},{id:"329385",title:"Dr.",name:"Rajesh K.",middleName:"Kumar",surname:"Singh",slug:"rajesh-k.-singh",fullName:"Rajesh K. Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329385/images/system/329385.png",biography:"Dr. Singh received a BPharm (2003) and MPharm (2005) from Panjab University, Chandigarh, India, and a Ph.D. (2013) from Punjab Technical University (PTU), Jalandhar, India. He has more than sixteen years of teaching experience and has supervised numerous postgraduate and Ph.D. students. He has to his credit more than seventy papers in SCI- and SCOPUS-indexed journals, fifty-five conference proceedings, four books, six Best Paper Awards, and five projects from different government agencies. He is currently an editorial board member of eight international journals and a reviewer for more than fifty scientific journals. He received Top Reviewer and Excellent Peer Reviewer Awards from Publons in 2016 and 2017, respectively. He is also on the panel of The International Reviewer for reviewing research proposals for grants from the Royal Society. He also serves as a Publons Academy mentor and Bentham brand ambassador.",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",country:{name:"India"}}},{id:"142388",title:"Dr.",name:"Thiago",middleName:"Gomes",surname:"Gomes Heck",slug:"thiago-gomes-heck",fullName:"Thiago Gomes Heck",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142388/images/7259_n.jpg",biography:null,institutionString:null,institution:{name:"Universidade Regional do Noroeste do Estado do Rio Grande do Sul",country:{name:"Brazil"}}},{id:"336273",title:"Assistant Prof.",name:"Janja",middleName:null,surname:"Zupan",slug:"janja-zupan",fullName:"Janja Zupan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/336273/images/14853_n.jpeg",biography:"Janja Zupan graduated in 2005 at the Department of Clinical Biochemistry (superviser prof. dr. Janja Marc) in the field of genetics of osteoporosis. Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"418340",title:"Dr.",name:"Jyotirmoi",middleName:null,surname:"Aich",slug:"jyotirmoi-aich",fullName:"Jyotirmoi Aich",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038Ugi5QAC/Profile_Picture_2022-04-15T07:48:28.png",biography:"Biotechnologist with 15 years of research including 6 years of teaching experience. Demonstrated record of scientific achievements through consistent publication record (H index = 13, with 874 citations) in high impact journals such as Nature Communications, Oncotarget, Annals of Oncology, PNAS, and AJRCCM, etc. Strong research professional with a post-doctorate from ACTREC where I gained experimental oncology experience in clinical settings and a doctorate from IGIB where I gained expertise in asthma pathophysiology. A well-trained biotechnologist with diverse experience on the bench across different research themes ranging from asthma to cancer and other infectious diseases. An individual with a strong commitment and innovative mindset. Have the ability to work on diverse projects such as regenerative and molecular medicine with an overall mindset of improving healthcare.",institutionString:"DY Patil Deemed to Be University",institution:null},{id:"349288",title:"Prof.",name:"Soumya",middleName:null,surname:"Basu",slug:"soumya-basu",fullName:"Soumya Basu",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035QxIDQA0/Profile_Picture_2022-04-15T07:47:01.jpg",biography:"Soumya Basu, Ph.D., is currently working as an Associate Professor at Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India. With 16+ years of trans-disciplinary research experience in Drug Design, development, and pre-clinical validation; 20+ research article publications in journals of repute, 9+ years of teaching experience, trained with cross-disciplinary education, Dr. Basu is a life-long learner and always thrives for new challenges.\r\nHer research area is the design and synthesis of small molecule partial agonists of PPAR-γ in lung cancer. She is also using artificial intelligence and deep learning methods to understand the exosomal miRNA’s role in cancer metastasis. Dr. Basu is the recipient of many awards including the Early Career Research Award from the Department of Science and Technology, Govt. of India. She is a reviewer of many journals like Molecular Biology Reports, Frontiers in Oncology, RSC Advances, PLOS ONE, Journal of Biomolecular Structure & Dynamics, Journal of Molecular Graphics and Modelling, etc. She has edited and authored/co-authored 21 journal papers, 3 book chapters, and 15 abstracts. She is a Board of Studies member at her university. She is a life member of 'The Cytometry Society”-in India and 'All India Cell Biology Society”- in India.",institutionString:"Dr. D.Y. Patil Vidyapeeth, Pune",institution:{name:"Dr. D.Y. Patil Vidyapeeth, Pune",country:{name:"India"}}},{id:"354817",title:"Dr.",name:"Anubhab",middleName:null,surname:"Mukherjee",slug:"anubhab-mukherjee",fullName:"Anubhab Mukherjee",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y0000365PbRQAU/ProfilePicture%202022-04-15%2005%3A11%3A18.480",biography:"A former member of Laboratory of Nanomedicine, Brigham and Women’s Hospital, Harvard University, Boston, USA, Dr. Anubhab Mukherjee is an ardent votary of science who strives to make an impact in the lives of those afflicted with cancer and other chronic/acute ailments. He completed his Ph.D. from CSIR-Indian Institute of Chemical Technology, Hyderabad, India, having been skilled with RNAi, liposomal drug delivery, preclinical cell and animal studies. He pursued post-doctoral research at College of Pharmacy, Health Science Center, Texas A & M University and was involved in another postdoctoral research at Department of Translational Neurosciences and Neurotherapeutics, John Wayne Cancer Institute, Santa Monica, California. In 2015, he worked in Harvard-MIT Health Sciences & Technology as a visiting scientist. He has substantial experience in nanotechnology-based formulation development and successfully served various Indian organizations to develop pharmaceuticals and nutraceutical products. He is an inventor in many US patents and an author in many peer-reviewed articles, book chapters and books published in various media of international repute. Dr. Mukherjee is currently serving as Principal Scientist, R&D at Esperer Onco Nutrition (EON) Pvt. Ltd. and heads the Hyderabad R&D center of the organization.",institutionString:"Esperer Onco Nutrition Pvt Ltd.",institution:null},{id:"319365",title:"Assistant Prof.",name:"Manash K.",middleName:null,surname:"Paul",slug:"manash-k.-paul",fullName:"Manash K. Paul",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/319365/images/system/319365.png",biography:"Manash K. Paul is a Principal Investigator and Scientist at the University of California Los Angeles. He has contributed significantly to the fields of stem cell biology, regenerative medicine, and lung cancer. His research focuses on various signaling processes involved in maintaining stem cell homeostasis during the injury-repair process, deciphering lung stem cell niche, pulmonary disease modeling, immuno-oncology, and drug discovery. He is currently investigating the role of extracellular vesicles in premalignant lung cell migration and detecting the metastatic phenotype of lung cancer via machine-learning-based analyses of exosomal signatures. Dr. Paul has published in more than fifty peer-reviewed international journals and is highly cited. He is the recipient of many awards, including the UCLA Vice Chancellor’s award, a senior member of the Institute of Electrical and Electronics Engineers (IEEE), and an editorial board member for several international journals.",institutionString:"University of California Los Angeles",institution:{name:"University of California Los Angeles",country:{name:"United States of America"}}},{id:"311457",title:"Dr.",name:"Júlia",middleName:null,surname:"Scherer Santos",slug:"julia-scherer-santos",fullName:"Júlia Scherer Santos",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311457/images/system/311457.jpg",biography:"Dr. Júlia Scherer Santos works in the areas of cosmetology, nanotechnology, pharmaceutical technology, beauty, and aesthetics. Dr. Santos also has experience as a professor of graduate courses. Graduated in Pharmacy, specialization in Cosmetology and Cosmeceuticals applied to aesthetics, specialization in Aesthetic and Cosmetic Health, and a doctorate in Pharmaceutical Nanotechnology. Teaching experience in Pharmacy and Aesthetics and Cosmetics courses. She works mainly on the following subjects: nanotechnology, cosmetology, pharmaceutical technology, aesthetics.",institutionString:"Universidade Federal de Juiz de Fora",institution:{name:"Universidade Federal de Juiz de Fora",country:{name:"Brazil"}}},{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",biography:"Dr. Kükürt graduated from Uludağ University in Turkey. He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals. He is currently working on the protective activity of phenolic compounds in disorders associated with oxidative stress and inflammation.",institutionString:null,institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"178366",title:"Dr.",name:"Volkan",middleName:null,surname:"Gelen",slug:"volkan-gelen",fullName:"Volkan Gelen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178366/images/system/178366.jpg",biography:"Volkan Gelen is a Physiology specialist who received his veterinary degree from Kafkas University in 2011. Between 2011-2015, he worked as an assistant at Atatürk University, Faculty of Veterinary Medicine, Department of Physiology. In 2016, he joined Kafkas University, Faculty of Veterinary Medicine, Department of Physiology as an assistant professor. Dr. Gelen has been engaged in various academic activities at Kafkas University since 2016. There he completed 5 projects and has 3 ongoing projects. He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329248",title:"Dr.",name:"Md. Faheem",middleName:null,surname:"Haider",slug:"md.-faheem-haider",fullName:"Md. Faheem Haider",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329248/images/system/329248.jpg",biography:"Dr. Md. Faheem Haider completed his BPharm in 2012 at Integral University, Lucknow, India. In 2014, he completed his MPharm with specialization in Pharmaceutics at Babasaheb Bhimrao Ambedkar University, Lucknow, India. He received his Ph.D. degree from Jamia Hamdard University, New Delhi, India, in 2018. He was selected for the GPAT six times and his best All India Rank was 34. Currently, he is an assistant professor at Integral University. Previously he was an assistant professor at IIMT University, Meerut, India. He has experience teaching DPharm, Pharm.D, BPharm, and MPharm students. He has more than five publications in reputed journals to his credit. Dr. Faheem’s research area is the development and characterization of nanoformulation for the delivery of drugs to various organs.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/system/329795.png",biography:"Dr. Mohd Aftab Siddiqui is an assistant professor in the Faculty of Pharmacy, Integral University, Lucknow, India, where he obtained a Ph.D. in Pharmacology in 2020. He also obtained a BPharm and MPharm from the same university in 2013 and 2015, respectively. His area of research is the pharmacological screening of herbal drugs/natural products in liver cancer and cardiac diseases. He is a member of many professional bodies and has guided many MPharm and PharmD research projects. Dr. Siddiqui has many national and international publications and one German patent to his credit.",institutionString:"Integral University",institution:null}]}},subseries:{item:{id:"15",type:"subseries",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.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11411,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. 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He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. 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We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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Valarmathi",profilePictureURL:"https://mts.intechopen.com/storage/users/69697/images/system/69697.jpg",institutionString:"Religen Inc. | A Life Science Company, United States of America",institution:null},{id:"205081",title:"Dr.",name:"Marco",middleName:"Vinícius",surname:"Chaud",fullName:"Marco Chaud",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSDGeQAO/Profile_Picture_1622624307737",institutionString:null,institution:{name:"Universidade de Sorocaba",institutionURL:null,country:{name:"Brazil"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"chapter.detail",path:"/chapters/28492",hash:"",query:{},params:{id:"28492"},fullPath:"/chapters/28492",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)}()