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These systems can be represented by a set of several equations, such as
In the chemical process industries, ammonia is one of the most widely manufactured inorganic compounds [3]. The majority of ammonia produced commercially is consumed in fertilizers, with the rest going into plastics, synthetic fibers and resins, pharmaceuticals, explosives, papers, and refrigeration [4]. As a result, modeling and optimization of ammonia synthesis process have received a significant attention from both the academia and industry. Ammonia is produced predominantly from the combination of elements such as nitrogen and hydrogen in a catalytic process using a promoted iron catalyst firstly established by Haber and Bosch as the reaction [4]:
The reaction is reversible and exothermic, releasing a significant amount of heat. In order to achieve a high conversion, the heat of the reaction should be removed. Therefore, the process is typically carried out in an autothermal synthesis reactor, in which the heat of reaction is utilized to preheat the feed gas and ensure the suitable temperature inside. The production of ammonia depends on several factors such as the reactor length, the operating pressure, temperature of the feed and reacted gas, the flow rate, and composition of the gas mixture. The optimization problem of the process is to maximize the economic return. Many studies discussing the modeling, simulation, and optimization of an autothermal ammonia synthesis reactor can be found in literature. Some of them can be mentioned here as in Babu et al. [5], Babu and Angira [6], Carvalho et al. [7], Edgar et al. [8], Ksasy et al. [9], Murase et al. [10], Upreti and Deb [11], Yusup et al. [12]. However, the model discussed in the studies of Edgar et al. [8], Murase et al. [10] has some minor errors and has been corrected in Upreti and Deb [11]. Moreover, the studies primarily focus on optimizing reactor length for a specific reactor top temperature, usually 694 K [6, 7, 12], or for a limited set of temperatures [9, 11]. However, as reported in some studies [11, 12], the economic return is determined by the top temperature and also the reactor length (the temperature of feed gas entering to the reaction zone). As a result, rather than a single variable problem of reactor length, the optimization problem should be viewed as a multivariable problem.
In the study [13], both the reactor length and the reactor top temperature are considered in the design variables for maximizing the profit return of the process. In order to solve the multivariate optimization problem, the cyclic coordinate search technique was employed. This method alters the value of one decision variable at a time, and for each coordinate direction, the golden section search was utilized to solve the single variable optimum problem. However, this traditional searching approach is prone to get caught in local optima. Therefore, the genetic algorithm has higher chance to obtain the global optimum profit of the process.
The system discussed here is an autothermal synthesis reactor, which is described in [10] and contains the correction of the objective function reported in [6, 11]. The feed gas contains 21.75 mole% nitrogen, 65.25 mole% hydrogen, 5.0 mole% ammonia, 4.0 mole% methane, and 4.0 mole% argon. In an autothermal reactor, the feed gas mixture enters from the bottom of the reactor, flows upward, enters the catalyst zone from the top, and moves downward. In the catalyst zone, the reaction takes place at around 500°C and 200 atm of pressure. The heat generated by the reaction is utilized to preheat the feed gas mixture in counter current flow. Figure 1 shows the schematic diagram of an autothermal ammonia synthesis reactor. The considered factors affecting the synthesis process are the temperature of feed gas at the entrance of the reaction zone (top temperature) and the reactor length. The goal of the optimal design is to determine the conditions that will give the highest economic return from the reactor operation.
Schematic diagram of an autothermal ammonia reactor [
The return of the process, which is calculated from the value of the product gas (heating value and ammonia value), subtract the cost of feed gas (as a source of heat only) and minus the amortization of reactor capital expenses, is the objective function for maximization (
in which,
The heat balance for the feed gas and the reacting gas and the mass balance for the nitrogen flow along the catalyst zone, respectively, give the mathematical model for the system:
in which
The differential equations are valid in the interval [0,
The notations
Other notations of the system are summarized in Table 1.
Notation | |
---|---|
Heat capacity of the feed gas | |
Heat capacity of the reacting gas | |
Catalyst activity | |
Δ | Heat of reaction |
Mass flow of component designed by subscript | |
Reaction rate constant | |
Partial pressure of component designated by subscript | |
Universal gas constant | |
Surface area of catalyst tubes per unit length of reactor | |
Cross-sectional area of catalyst zone | |
Overall heat transfer coefficient | |
Total mass transfer flow rate |
Notation of the synthesis system.
The variables are subjected to the following physical constraints, as is typical in industries [10]:
The length of the reactor and the top temperature are chosen as the design variables. The remaining variables (
The optimal design problem is summarized as follows:
The system of ordinary differential Eqs. (3), (4), and (5) with initial conditions (11) was solved by Runge–Kutta fourth-order method. The system is well defined when the top temperature (
The range of the design variables is
In barrier or penalty methods, the objective function will receive an undesired value when one of the constraints is violated. Therefore, the solution will be kept in the feasible region. The objective function has been modified as
Figure 2 shows the fitness values as a function of generation. As can be observed, the fitness function value achieved the highest after roughly 20 generations and then stayed unchanged. After 100 generations, it was obtained that the reactor length should be 6.772 m, and the top temperature should be 707.09 K. The process produces a profit of 5.018× 106 $ per year. The other parameters of the process are summarized in Table 3 and compared with the findings of a cyclic coordinate search [13]. The profit value is slightly higher than those reported in the literature, which focused solely on reactor length optimization. From the results, the temperature at the entrance of the catalyst zone should be slightly higher, and that the reactor length should also be slightly longer than previously reported.
Fitness value versus generations.
Variables | Interval | Cyclic coordinate [13] | Genetic algorithm |
---|---|---|---|
[0,10] | 6.724 | 6.772 | |
[600,800] | 700.27 | 707.09 | |
[400,800] | 400.00 | 401.09 | |
629.94 | 631.12 | ||
[0,3220] | 490.68 | 490.68 | |
5.018 | 5.018 |
Maximization results.
The behavior of permeate flux has a significant impact on the performance of cross-flow ultrafiltration. Many factors cause flux declination, such as solution properties, membrane properties, and operation conditions. The majority of current research has centered on increasing membrane performance in terms of permeability and selectivity [14, 15]. Just a few studies have paid attention to the configuration and operation of the membrane module [16].
Various factors determine the decision of membrane module geometry for a given application, including fabrication method, power consumption, and fouling potential [17]. Manufacturers frequently recommend the membrane module design from the fabrication standpoint [17]. There is virtually no evidence that their approach prioritizes the energy efficiency. Currently, with a growing in energy concern and a falling in membrane cost, the membrane module design should place a higher attention on energy efficiency. As a result, it is necessary to propose a module design methodology that takes into account the energy factor.
Furthermore, membrane operating conditions are usually decided by user experience, a handbook, or a manual from the membrane supplier. However, the permeate flux equation governing the performance of the membrane system varies greatly between different situations. In this aspect, for any specific application, a general methodology for the design and operation conditions should be studied.
In cross-flow ultrafiltration of protein solution, Nguyen et al. [18] proposed a simple combined model, which simultaneously considers pore blockage and cake filtration, to describe the flux declination. Then, in the study [19], the correlation between the steady-state permeate flux and operation parameters was reported. From the steady-state operation equation, optimal design and operation conditions for each particular application could be established.
However, just a few reports on the optimization of membrane processes and cost estimation have been published, or the cost estimation is too general. For example, Wiley et al. [17] optimized the membrane module configurations for brackish water desalination. However, the operation mode is single-pass and only the membrane cost and energy cost were taken into account. Sethi and Wiesner [20] developed the cost model for the removal of natural organic matter, but the study has not conducted the optimization. In membrane technology, the feed and bleed operation mode, which combines the batch and the single-pass configurations, is commonly utilized for continuous full-scale filtration [21, 22]. Therefore, the optimization of a membrane module operated in feed and bleed mode for protein ultrafiltration is considered. The membrane geometry dimensions and operating conditions are design variables in the problem. The system is represented by a set of ordinary differential equations. The objective function is the annual cost, which consists of various types of capital investments and an operating expense. The capital investments are classified into several categories, which are individually correlated to plant scale, particularly the membrane area. The operating expense is the power consumption.
The configuration of filtration system is continuous feed and bleed, which is shown schematically in Figure 3. The notations are summarized in Table 4. There are two main pumps in this operation: the feed pump provides the necessary trans-membrane pressure, while the recirculation pump maintains the cross-flow rate through the modules. The concentrate is continually withdrawn from the system at a flow rate (
Schematic configuration of feed-and-bleed mode membrane system.
Notation | Name and units |
---|---|
Feed flow rate [m3/hr] | |
Retentate (concentrate) flow rate [m3/hr] | |
Recirculation flow rate [m3/hr] | |
Flow rate in membrane module [m3/hr] | |
Permeation flow rate [m3/hr] | |
Pressure at outlet of feed pump [kPa] | |
Pressure at the inlet of membrane module [kPa] | |
Pressure at the inlet of membrane module [kPa] | |
Energy consumed by the feed pump [kW] | |
Energy consumed by the recirculation pump [kW] | |
Initial concentration of protein solution [m3/m3] | |
Inlet concentration of protein solution [m3/m3] | |
Final concentration of protein solution [m3/m3] | |
Concentration of protein in permeate flux [m3/m3] | |
Fluid flow velocity [m/s] | |
Fluid density [kg/m3] | |
Fluid viscosity [kg/(m·s)] | |
Width, height, length, hydraulic diameter of the membrane module |
Summary of system configuration notations.
The material balance for total mass and protein give:
The viscosity and density of protein solution correlate to its concentration [23]:
in which,
The permeate flux through the membrane is [19].
in which
The equation for permeate flux can be rewritten as:
or in terms of shear rate
The flow rate/velocity drop and channel length change are calculated from the total mass balance and component balance within the control volume
The pressure loss is estimated by the Darcy-Weisbach Equation [24, 25].
in which
The set of ordinary equations that describes the membrane module system was established as follows [26].
in the range of concentration [
The system of the ordinary equations can be solved numerically by Runge–Kutta fourth-order method [27] to obtain the flow rate, the length, and the pressure. From that, the two important factors determining the total cost, membrane area, and total energy were calculated:
In this equation,
Δ
The operating cost consists of power consumption of the pumps and membrane replacement. The annual energy expense of the pumps is calculated as
The membrane replacement cost is calculated as
where
The membrane price is usually about 200 $/m2 ([9]), and membrane life is 12–18 months. Therefore, the membrane replacement cost per year is roughly estimated as 200 $/m2/year for the interest of
It is widely observed that capital costs are correlated to the size in the power-law form [30]:
In order to achieve higher accuracy, rather than simply predicting the whole capital cost of the membrane plant to capacity, Sethi and Wiesner [20] divided the capital investment into several major categories, which was correlated to the size independently. The major categories include pumps and other manufactured equipment.
Pump capital cost
The pumps capital cost can be estimated as (Perry et al. [31]):
in which.
The cost index,
The pump size (
Capital cost of other equipment
In membrane application, the membrane area is the key parameter, which determines the plant capacity [34]. Thus, the membrane area is chosen as the basic for the estimation of various components in the capital costs.
Non-membrane equipment and facilities, excluding the pumps, were grouped into four main categories: (1) pipes and valves; (2) instruments and controls; (3) tanks and frames; and (4) miscellaneous. The capital cost of each is correlated to the membrane area as follows (Sethi and Wiesner [20])
Pipes and valves
Instruments and controls
Tanks and frames
Miscellaneous
Annual capital cost
The capital cost can be annualized using the amortization factor as
For the plant design year of 20 years and the interest rate 8%, the amortization factor will be about 0.1.
In the problem, some variables, called input variables, are fixed due to the requirement of the design. In membrane design, these are feed flow
The design variables were: channel geometry (width × length × height), the inlet pressure (
The objective function is the sum of capital cost and operating cost, which were annualized:
The pressure at the outlet point should be positive. This constraint is satisfied by assigning a high value to the objective function if the outlet pressure is negative.
The decision variables are frequently limited on a finite range
in which
The system parameters and variables are summarized in Table 5.
Parameters | Value |
---|---|
Feed flow rate (m3/hr) | 0.02–200 |
Inlet pressure (kPa) | 200–1000 |
Recirculation flow rate (m3/hr) | 0–50 |
Initial solid fraction (m3/m3) | 0.1 |
Final solid fraction (m3/m3) | 0.4 |
Plant design year (year) | 20 |
Interest rate (%) | 8 |
Energy price ($/kWh) | 0.08 |
Efficiency of pumps (%) | 70 |
Operating temperature (°C) | 25 |
Module height (mm) | 0–100 |
Module width (m) | 0–30 |
System parameters and variables.
The parameters of GA such as population size, crossover probability, mutation probability values were set to be, 100, 1.0, and 0.30, respectively. The selection was based on roulette wheel with elitism, which means the most fit individual is guaranteed a place in the next generation. The number of generations was assigned to be 500. Because the problem is to minimize the cost, the fitness function was defined as:
For the demonstration of this method, optimum designs of several feed flow rates have been carried out. The lower limit of the membrane width is 0.1 m, the lower limit for the module height is 0.5 mm. The designs are shown in Table 6.
Feed [m3/hr] | Pressure [kPa] | Recirculation [m3/hr] | width [m] | height [mm] | total cost [$/yr] | ||
---|---|---|---|---|---|---|---|
0.02 | 0.1 | 0.4 | 523 | 2.8 | 0.1 | 5.0 | 1.29 × 103 |
0.2 | 0.1 | 0.4 | 1000 | 4.9 | 0.1 | 8.9 | 4.30 × 103 |
2 | 0.1 | 0.4 | 1000 | 0.2 | 0.1 | 6.9 | 1.18 × 104 |
20 | 0.1 | 0.4 | 987 | 0.2 | 1.3 | 5.0 | 5.60 × 104 |
200 | 0.1 | 0.4 | 1000 | 0.8 | 11.1 | 5.0 | 3.65 × 105 |
Optimum designs of membrane module.
Figure 4 presents the optimum total cost per unit of feed flow. The cost per unit of feed flow decreases with an increase in plant capacity. It reflects the economies of scale.
The behavior of cost per unit flow rate design in optimum condition with plant capacity.
The results also suggest that the membrane module dimensions and operation condition will change greatly depending on the process requirements, such as the required feed capacity. It is challenging to predict the direction. It might be concluded that the permeate flux also greatly affects the geometric design and operation strategy in membrane separation processes. It is difficult to find a general rule for the design, for each specific system, the correlation between the permeate flux and operating conditions and membrane geometry should be investigated.
Fuel cells that are highly effective and green technology for converting chemical energy stored in fuel to useable power are currently regarded as one of the most promising approaches for future energy requirements [35]. The solid oxide fuel cell (SOFC) has demonstrated an exceptional integration of advantages, such as high efficiency, fuel flexibility, wide contamination acceptance, and low pollution [36, 37]. Modeling and simulation are valuable tools for determining the impact of various design factors and operating conditions on cell performance, as well as for improving fuel cells [38, 39, 40]. Plenty of models have been reported to add to the understanding of fuel cells. Modeling approaches can be categorized into two types: theoretical and empirical one [39, 41, 42]. In the theoretical approach, the spatial dimensions of the models range from simple 0 (0-D) [43, 44] and 1 (1-D) [42, 45, 46, 47], to more complicated 2 (2-D) [48, 49, 50, 51] and 3 (3-D) [52, 53, 54], all with various characteristics and directed at different objectives. The mathematical models, which are based on conservation principles, require a lot of data on parameters and properties of fuel cell, as well as complicated equations and time-consuming calculation.
Empirical or data-driven approach may be more feasible for fuel cell users since the behavior can be quickly and simply deduced without a comprehensive understanding of the internal components, just based on the experimental data [39, 41]. Least squares support vector machine (LS-SVM) [55], Hammerstein model [56, 57] are examples of these approaches. In this approach, artificial neural network (ANN) shows several advantages, including high nonlinearity, rapid computation, a low degree of error in matching experimental data. Using ANNs to model SOFCs appears to be a very promising method.
In this section, an ANN was used to model the performance of the BSCF/GDC-based cathode SOFC. The cell voltage was predicted from cathode sintering temperature, cell operating temperature, and cell current. Several network architectures were examined to find the best structure, and the network was trained using back-propagation methods. The data for training, validation, and testing were taken from our study [58]. The genetic algorithm and the developed ANN were then used to find the best conditions for achieving maximum power.
Artificial neural networks (ANNs), which were analogous to biological nervous systems, consist of interconnected nodes known as neurons to receive and transfer data [59]. The most basic form, feed-forward architecture, is made up of an input layer, one hidden layers, and an output layer. The input and output layers have the same number of neurons as the number of inputs and outputs in the system to be modeled. Weighted connections connect each neuron to every other neuron in the next layer. In any layer except the input, the weighted sum of data from the previous layer is the input of a neuron. The neuron then activates the data using a function and transfers the response to all neurons in the next layer. The size of the hidden layers is a significant factor that affects the estimation precision because it can make the network become insufficient or overfitting [60]. The number of neurons in hidden layer is generally determined through trials. Figure 5 illustrates a 3–5-1 feed forward artificial neural network with operating temperature, sintering temperature, and current as inputs.
Artificial neural network (3–5-1) structure.
The activation function employed in this model is the logistic sigmoid
The input data (
in which xmax and xmin are the bounded interval of the experimental data.
To assess the performance of ANN, the mean squared error (MSE) and coefficient of determination (R2) are usually used [61].
Various factors affect the performance of fuel cells such as cathode and anode structure, electrolyte material and thickness, cell temperature, inlet and outlet gas compositions. Two important factors, cathode sintered temperature and cell operating temperature, were considered in this model. The sintered temperature is from 1000–1050°C, whereas the operating temperature ranges from 625–700°C. The sintered temperature affects the structure of the obtained cathode as reported in [58]. The explanation of the range for the investigated parameters can be found in [62].
An ANN with one input layer, one hidden layer, and one single output layer was proposed. Current density, sintered temperature of the cathode, and cell operating temperature are the inputs. Back-propagation algorithm [63] was used to train the network. The maximum number of iteration and minimum performance gradient were set to 400 and 10−5, respectively, to stop the training. The proper network structure is determined through a series of trial tests. The data were split into three subsets at random: training, validation, and test, each containing 70, 20, 10% of the total samples, respectively. The validation and test sets are necessary for evaluating the validation and power of the networks.
The parameters of the neural network were saved and utilized in the next stage to optimize the power density using genetic algorithms.
The objective function is the power density of the fuel cell
where
The design variables and their corresponding ranges are summarized as follows:
sintered temperature of the cathode, [1000–1050] (°C).
operating temperature of the cell, [625–700] (°C).
electric current of the cell, [0–1500] (mA.cm−2)
The parameters of GA as population size, mutation probability values were set to be 100 and 0.10, respectively. The survival of the individuals was decided by roulette wheel with elitism. The number of generations was 500.
Figure 6 depicts the fitness values (maximum and mean) of the population versus generation. As indicated in the figure, after about 20 generations, the value of fitness function attained to a maximum value and then remained unchanged. After 100 generations, the maximum fuel cell power density of 451.64 mW/cm2 could be achieved at the sintered temperature of 1005°C, operating temperature of 668°C, and current density of 777 mA/cm2.
The fitness values versus generation.
The application of genetic algorithm in chemical engineering processes has been illustrated by three case studies. The results suggest that the optimum conditions of complex chemical problems can be easily obtained using genetic algorithm. The successes of genetic algorithm for the challenging problems reported herein, the development of many faster and flexible versions of GA, the improvement of computing ability all suggest the continually increasing impact of metaheuristic methods in chemical engineering systems.
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Nutrition",value:20,count:2},{group:"subseries",caption:"Animal Reproductive Biology and Technology",value:28,count:4},{group:"subseries",caption:"Animal Science",value:19,count:5}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:3},{group:"publicationYear",caption:"2021",value:2021,count:3},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:1},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:229,paginationItems:[{id:"318170",title:"Dr.",name:"Aneesa",middleName:null,surname:"Moolla",slug:"aneesa-moolla",fullName:"Aneesa Moolla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/318170/images/system/318170.png",biography:"Dr. Aneesa Moolla has extensive experience in the diverse fields of health care having previously worked in dental private practice, at the Red Cross Flying Doctors association, and in healthcare corporate settings. She is now a lecturer at the University of Witwatersrand, South Africa, and a principal researcher at the Health Economics and Epidemiology Research Office (HE2RO), South Africa. Dr. Moolla holds a Ph.D. in Psychology with her research being focused on mental health and resilience. In her professional work capacity, her research has further expanded into the fields of early childhood development, mental health, the HIV and TB care cascades, as well as COVID. She is also a UNESCO-trained International Bioethics Facilitator.",institutionString:"University of the Witwatersrand",institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038WgMKQA0/Profile_Picture_2022-06-02T11:44:20.jpg",biography:"Dr. Sergio Alexandre Gehrke is a doctorate holder in two fields. The first is a Ph.D. in Cellular and Molecular Biology from the Pontificia Catholic University, Porto Alegre, Brazil, in 2010 and the other is an International Ph.D. in Bioengineering from the Universidad Miguel Hernandez, Elche/Alicante, Spain, obtained in 2020. In 2018, he completed a postdoctoral fellowship in Materials Engineering in the NUCLEMAT of the Pontificia Catholic University, Porto Alegre, Brazil. He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",country:{name:"Spain"}}},{id:"342152",title:"Dr.",name:"Santo",middleName:null,surname:"Grace Umesh",slug:"santo-grace-umesh",fullName:"Santo Grace Umesh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/342152/images/16311_n.jpg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"333647",title:"Dr.",name:"Shreya",middleName:null,surname:"Kishore",slug:"shreya-kishore",fullName:"Shreya Kishore",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333647/images/14701_n.jpg",biography:"Dr. Shreya Kishore completed her Bachelor in Dental Surgery in Chettinad Dental College and Research Institute, Chennai, and her Master of Dental Surgery (Orthodontics) in Saveetha Dental College, Chennai. She is also Invisalign certified. She’s working as a Senior Lecturer in the Department of Orthodontics, SRM Dental College since November 2019. She is actively involved in teaching orthodontics to the undergraduates and the postgraduates. Her clinical research topics include new orthodontic brackets, fixed appliances and TADs. She’s published 4 articles in well renowned indexed journals and has a published patency of her own. Her private practice is currently limited to orthodontics and works as a consultant in various clinics.",institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"323731",title:"Prof.",name:"Deepak M.",middleName:"Macchindra",surname:"Vikhe",slug:"deepak-m.-vikhe",fullName:"Deepak M. Vikhe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/323731/images/13613_n.jpg",biography:"Dr Deepak M.Vikhe .\n\n\t\n\tDr Deepak M.Vikhe , completed his Masters & PhD in Prosthodontics from Rural Dental College, Loni securing third rank in the Pravara Institute of Medical Sciences Deemed University. He was awarded Dr.G.C.DAS Memorial Award for Research on Implants at 39th IPS conference Dubai (U A E).He has two patents under his name. He has received Dr.Saraswati medal award for best research for implant study in 2017.He has received Fully funded scholarship to Spain ,university of Santiago de Compostela. He has completed fellowship in Implantlogy from Noble Biocare. \nHe has attended various conferences and CDE programmes and has national publications to his credit. His field of interest is in Implant supported prosthesis. Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Univeristy of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:null},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:null},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. 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He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). 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:"chapter.detail",path:"/chapters/37356",hash:"",query:{},params:{id:"37356"},fullPath:"/chapters/37356",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)}()