ENGLISH

Artificial Intelligence Technologies for Computational Biology

By Ranjeet Kumar Rout , Saiyed Umer , Sabha Sheikh , Amrit Lal Sangal

Book information

Publisher
CRC Press
Year
2022
ISBN
1032160004, 9781032160009
Language
english
Format
PDF
Filesize
29 MB (30413547 bytes)
Pages
344\345
Topic
Biology
Time added
2022-08-31 10:44:56

Description

This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing. It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems. The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology. This book: • Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis. • Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems. • Presents the application of evolutionary computations for fractal visualization of sequence data. • Explores the use of genetic algorithms for pair-wise and multiple sequence alignments. • Examines the roles of efficient computational techniques in biology. Cover Half Title Title Page Copyright Page Contents Preface Contributors List of Figures List of Tables Chapter 1: Graph Representation Learning for Protein Classification Chapter 2: Extraction of Sequence-Based Features for Prediction of Methylation Sites in Protein Sequences Chapter 3: A Taxonomy of e-Healthcare Techniques and Solutions: Challenges and Future Directions Chapter 4: Classification of Lung Diseases Using Machine Learning Techniques Chapter 5: Multi Objective Bacterial Foraging Optimization: A Survey Chapter 6: Artificial Intelligence for Biomedical Informatics Chapter 7: A Novel Approach for Feature Selection Using Artificial Neural Networks and Particle Swarm Optimization Chapter 8: In Search for the Optimal Preprocessing Technique for Deep Learning-Based Diabetic Retinopathy Stage Classification from Retinal Fundus Images Chapter 9: Cancer Diagnosis from Histopathology Images Using Deep Learning: A Review Chapter 10: Skin Lesion Classification by Using Deep Tree-CNN Chapter 11: Hybrid Deep Learning Model to Diagnose Covid-19 on its Early Stages Using Lung CT Images Chapter 12: Impact of Machine Learning Practices on Biomedical Informatics, Its Challenges and Future Benefits Chapter 13: Recognition of Types of Arrhythmia: An Implementation of Ensembling Techniques Using ECG Beat Chapter 14: Feature Selection, Machine Learning and Deep Learning Algorithms on Multi-modal Omics Data Index

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