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Machine Learning and Systems Biology in Genomics and Health

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  • © 2022

Overview

  • Gives insights into the key features of Deep Learning and Machine Learning
  • Provides innovative computing solutions in Genomics
  • Discusses important topics like precision medicine and AI for biomarker discovery

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Table of contents (9 chapters)

Keywords

About this book

This book discusses the application of machine learning in genomics. Machine Learning offers ample opportunities for Big Data to be assimilated and comprehended effectively using different frameworks. Stratification, diagnosis, classification and survival predictions encompass the different health care regimes representing unique challenges for data pre-processing, model training, refinement of the systems with clinical implications. The book discusses different models for in-depth analysis of different conditions. Machine Learning techniques have revolutionized genomic analysis. Different chapters of the book describe the role of Artificial Intelligence in clinical and genomic diagnostics. It discusses how systems biology is exploited in identifying the genetic markers for drug discovery and disease identification. Myriad number of diseases whether be infectious, metabolic, cancer can be dealt in effectively which combines the different omics data for precision medicine. Major breakthroughs in the field would help reflect more new innovations which are at their pinnacle stage. 


This book is useful for researchers in the fields of genomics, genetics, computational biology and bioinformatics.

Editors and Affiliations

  • Department of Pathogenesis and Cellular Response, National Centre for Cell Science, Pune, India

    Shailza Singh

About the editor

Dr. Shailza Singh is  Scientist-E and Incharge of Bioinformatics and High Performance Computing Facility, National Centre for Cell Science, Pune, India Her research chiefly focuses on systems and synthetic biology. She also specializes in infectious diseases such as leishmaniasis. Her research group is working to integrate the action of regulatory circuits, cross-talk between pathways, and non-linear kinetics of biochemical processes through mathematical modeling. Dr. Singh has been honored with the DBT-RGYI, DST Young Scientist and INSA Bilateral Exchange Programme awards, and was selected by the DBT for a SAKURA EXCHANGE Programme in Science in the field of Artificial Intelligence and Machine learning to Tokyo in 2018. She serves as a reviewer for prestigious international grants such as the Research Councils UK; for national grants from the DBT, DST and CSIR; and for several prominent international journals, e.g. Parasite and Vectors, PLOS One, BMC Infectious Disease, BMC Research Notes, Oncotarget, and the International Journal of Cancer.

Bibliographic Information

  • Book Title: Machine Learning and Systems Biology in Genomics and Health

  • Editors: Shailza Singh

  • DOI: https://doi.org/10.1007/978-981-16-5993-5

  • Publisher: Springer Singapore

  • eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022

  • Hardcover ISBN: 978-981-16-5992-8Published: 05 February 2022

  • Softcover ISBN: 978-981-16-5995-9Published: 06 February 2023

  • eBook ISBN: 978-981-16-5993-5Published: 04 February 2022

  • Edition Number: 1

  • Number of Pages: VII, 236

  • Number of Illustrations: 1 b/w illustrations

  • Topics: Genetics and Genomics, Bioinformatics, Biological Techniques, Cancer Research

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