Applied Computational Biology and Statistics in Biotechnology and Bioinformatics (Set of 2 Vols.) 1st Edition

The book Bioinformatics and Computational Biology: Concepts, Methods, and Applications is designed to meet the growing needs of academia, researchers, and commercial ventures. It is divided into forty-four chapters, which are organized into six broad sections: Bioinformatics, Genomics and Proteomics, Phylogeny, Drug Design and Epigenomics, Advanced Computational Tools and Techniques, and Statistical Methods for Computational Biology, Data Mining, and Visualization. The final section addresses Socio Economics and Ethics. This book provides an introduction to the fundamental problems in computational molecular biology and bioinformatics, and includes basic molecular biology concepts, tools, techniques, and ways to measure sequence similarity. It also presents simple applications of searching sequence databases, methods for aligning multiple biological sequences and genomes, and the problem of gene expression and motif finding. The text aims to introduce computational biology without using formulas, presenting the biological and computational ideas in a relatively simple manner. The book focuses on computational and statistical principles applied to genomes, and introduces the computational statistics that are essential for understanding and visualization of problems. This makes the material accessible to statisticians and computer scientists without biological training, as well as to biologists with limited background in statistics and computer science. A dedicated chapter has been exclusively devoted to computational biology and computational statistics as applied in biotechnology, illustrated with methodology, application, and interpretation of results. The book contains more than four hundred figures, illustrations, and diagrams that reinforce concepts and present key results from the primary literature, making it a valuable resource for those working in the biotechnology sector, particularly researchers working in the laboratories of ICAR, CSIR, SAU, and many more institutions engaged in R&D activities.