Computational and Analytic Methods in Biological Sciences : Bioinformatics with Machine Learning and Mathematical Modelling /

Bibliographic Details
Corporate Author:	Taylor & Francis
Other Authors:	Makrariya, Akshara (Editor)
Format:	eBook
Language:	English
Published:	Gistrup, Denmark : River Publishers, [2023]
Subjects:	Bioinformatics. Machine learning. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
List of Figures
List of Tables
List of Contributors
List of Abbreviations
Chapter 1: Modeling of Smoking Transmission Dynamics using Caputo-Fabrizio Type Fractional Derivative
1.1: Introduction
1.2: Basic Concept of Fractional Operators
1.3: Model Formulation
1.4: Caputo-Fabrizio Fractional Order Derivative
1.4.1: Stability Analysis of Model by Using Fixed-Point Theory
1.5: Numerical Results and Discussion
1.6: Conclusion
References
Chapter 2: Hybrid Feature Selection Techniques Utilizing Soft Computing Methods for Classifying Microarray Cancer Data
2.1: Introduction
2.2: Proposed Framework
2.2.1: Genes Extraction by ICA
2.2.2: Genetic Bee Colony (GBC) Algorithm
2.3: Used Classifier
2.3.1: Naive Bayes Classifier (NBC)
2.3.2: Support Vector Machine (SVM) Classifier
2.4: Experimental Setups
2.5: Experimental Result
2.6: Conclusion
References
Chapter 3: Finite Element Technique to Explicate Calcium Diffusion in Alzheimer's Disease
3.1: Introduction
3.2: Literature Survey
3.3: Mathematical Formulations
3.3.1: Calcium Buffering
3.3.2: Voltage Gated Calcium Channel (VGCC)
3.3.3: Endoplasmic Reticulum (ER)
3.4: The Finite Element Technique
3.4.1: Approximated Geometry of the Cell
3.4.2: Physiological Boundary Conditions
3.4.3: Meshing of the domain
3.5: Results and Discussion
3.5.1: For Hippocampal Neuron
3.5.2: For Basal Forebrain Neuron
3.6: Conclusion
References
Chapter 4: Comparative Analysis of Computational Methods used in Protein-Protein Interaction (PPI) Studies
4.1: Introduction
4.1.1: Protein
4.1.2: Protein-Protein Interaction
4.1.2.1: Protein-protein interfacial characteristics
4.1.2.1.1: Size and shape.
4.1.2.1.2: Complementarity between surfaces
4.1.2.1.3: Residue interface propensities
4.1.2.1.4: Hydrophobicity including Hydrogen bonding
4.1.2.1.5: Segmentation and secondary structure
4.1.2.1.6: Conformational changes on complex formation
4.1.2.2: PPI types
4.1.2.2.1: Homo oligomeric and Hetero oligomeric
4.1.2.2.2: Obligate and non obligate complexes
4.1.2.2.3: Transient and permanent complexes
4.1.2.2.4: Disordered to ordered complexes
4.1.2.3: PPI methods classification
4.2: In Silico Methods
4.2.1: Sequence Based Approaches
4.2.1.1: Ortholog based sequence approach
4.2.1.2: Domain pairs-based sequence approach
4.2.1.3: Statistical sequence-based approaches
4.2.1.3.1: Mirror tree method
4.2.1.3.2: PIPE
4.2.1.3.3: Co-evolutionary divergence
4.2.1.4: Machine learning sequence-based approaches
4.2.1.4.1: Auto-covariance
4.2.1.4.2: Pairwise similarity
4.2.1.4.3: Amino acid composition
4.2.1.4.4: Amino acid triad
4.2.1.4.5: UNISPPI
4.2.1.4.6: ETB viterbi
4.2.2: Structure Based Approaches
4.2.2.1: Template structure-based approaches
4.2.2.1.1: PRISM
4.2.2.1.2: PREPPI
4.2.2.2: Statistical structure-based approach
4.2.2.2.1: PID matrix score
4.2.2.2.2: Pre SPI
4.2.2.2.3: Domain cohesion and coupling
4.2.2.2.4: MEGADOCK
4.2.2.2.5: MetaApproach
4.2.2.3: Machine learning structure-based approaches
4.2.2.3.1: Random forest
4.2.2.3.2: Struct2Net
4.2.3: Gene Neighbourhood
4.2.4: Gene Fusion
4.2.5: In Silico Two-hybrid (I2h)
4.2.6: Phylogenetic Tree
4.2.7: Phylogenetic Profile
4.2.8: Gene Expression
4.3: PPI Networks and Databases
4.3.1: Creation of the PPI Networks
4.3.1.1: Choice of databases and data selection
4.3.1.2: Visualising PPI network
4.3.2: Different Databases
4.3.2.1: Interaction database.
4.3.2.2: Metamining databases
4.3.2.3: Predictive interaction databases
4.3.2.4: Pathway database
4.3.2.5: Unifying database
4.4: Softwares Available for PPI
4.5: Conclusion
References
Chapter 5: Optimization of COVID-19 Risk Factors Using Fuzzy Logic Inference System
5.1: Introduction
5.2: Methodology
5.2.1: Proposed Mamdani Fuzzy Control System
5.2.2: Fuzzy Controller Design
5.2.3: Parameters Identification
5.2.4: Fuzzification
5.2.5: Fuzzy Inference Rule Base
5.2.6: Rule Evaluation By Fuzzy Inference Engine
5.2.7: Defuzzification
5.3: Results
5.4: Discussion
5.5: Conclusion and Future Work
References
Chapter 6: Dynamical Analysis of the Fractional-Order Mathematical Model of Hashimoto's Thyroiditis
6.1: Introduction
6.2: Preliminaries
6.3: Formulation of Fractional-Order Model of Hashimoto's Thyroiditis
6.4: Stability Analysis
6.5: Construction of a Numerical Solution Scheme
6.6: Numerical Segment
6.7: Conclusions
References
Chapter 7: Heated Laminar Vertical Jet of Pseudoplastic Fluids-Against Gravity
7.1: Introduction
7.2: Basic Equations
7.3: Results and Discussions
7.4: Graphical Presentation
7.5: Conclusion
References
Chapter 8: Analytical Solutions For Hydromagnetic Flow of Chemically Reacting Williamson Fluid Over a Vertical Cone and Wedge with Heat Source/Sink
8.1: Introduction
8.2: Formulation of the Problem
8.3: Solution of the Problem
8.4: Results and Discussion
8.5: Conclusion
References
Chapter 9: Aboodh Transform Homotopy Perturbation Method for Solving Newell-Whitehead-Segel Equation
9.1: Introduction
9.2: Basic Definition of Aboodh Transform
9.2.1: Some Properies of Aboodh Transform
9.3: Idea of Aboodh Transform Homotopy Perturbation Method
9.4: Some Illustrations
9.5: Conclusion.
Chapter 13: Analysis of One-Dimensional Groundwater Recharge by Spreading using Hybrid Differential Transform and Finite Difference Method
13.1: Introduction
13.2: Research Gap
13.3: Mathematical Formulation
13.4: Methodology
13.5: Hybrid Differential Transform and Finite Difference Method
13.6: Solution
13.7: Results and Discussion
13.8: Conclusions
13.9: Utilities of Research
References
Chapter 14: Numerical Solution of Physiological Thermoregulatory Disturbances in Cold Environment
14.1: Introduction
14.2: Material and Methods
14.3: Result
14.4: Discussion
References
Chapter 15: Mathematical Modelling of Transient Heat Conduction in Biological System by Finite Element Method and Coding in MATLAB
15.1: Introduction
15.2: General Procedure of Finite Element Method
15.3: Process of Finite Element Method
15.3.1: Definition of the Problem and its Domain: One Dimensional Thermal Equation of Biological System
15.4: Steps Involved in Finite Element Process
15.5: Model-2: One Dimensional Quadratic Interpolation Model
15.5.1: Assumption of a Suitable form of Variation in T for Quadratic Element
15.6: Assembly of Elements
15.7: Matrix Form of Element Equation
15.8: Algorithm and Computer Program to Solve Heat Equation using FEM in Matlab:
15.9: Result and Discussion
References
Index
About the Editors.