Data Science for Genomics: A Comprehensive Guide

By Amit Kumar Tyagi, this book presents the foundational concepts of data science as they pertain to genomics, encompassing the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.

Foundational Concepts of Data Science

Sections cover Data Science, Machine Learning, Deep Learning, data analysis, and visualization techniques. These concepts are crucial for understanding the process of data inspection, cleaning, transformation, and modeling.

Genomics, Genetics, Transcriptomes, and Proteomes

The authors then present the fundamentals of Genomics, Genetics, Transcriptomes, and Proteomes as basic concepts of molecular biology, along with DNA and key features of the human genome, as well as the genomes of eukaryotes and prokaryotes.

Techniques for Studying Genomes

Techniques that are more specifically used for studying genomes are then described in the order in which they are used in a genome project, including methods for constructing genetic and physical maps. DNA sequencing methodology and the strategies used to assemble a contiguous genome sequence and methods for identifying genes in a genome sequence and determining the functions of those genes in the cell.

Information Release and Data Security

Readers will learn how the information contained in the genome is released and made available to the cell, as well as methods centered on cloning and PCR. The book also discusses Blockchain technology for securing data at end user/server side, ensuring data privacy and integrity.

Real-World Case Studies and Future Directions

The book includes topics such as real-world case studies, open issues and challenges faced in Genomics, including future research directions and a separate chapter for Ethical Concerns, providing a comprehensive overview of the field.

Published by Elsevier Science on November 27, 2022, this book is a valuable resource for researchers, students, and professionals in the field of genomics and data science.