Immunoinformatics of Cancers: Practical Machine Learning Approaches Using R - Softcover

Rezaei MD PhD, Nima; Jabbari, Parnian

Softcover

ISBN 10: 0128224002 ISBN 13: 9780128224007

Publisher: Academic Press, 2022

Synopsis

Immunoinformatics of Cancers: Practical Machine Learning Approaches Using R takes a bioinformatics approach to understanding and researching the immunological aspects of malignancies. It details biological and computational principles and the current applications of bioinformatic approaches in the study of human malignancies. Three sections cover the role of immunology in cancers and bioinformatics, including databases and tools, R programming and useful packages, and present the foundations of machine learning. The book then gives practical examples to illuminate the application of immunoinformatics to cancer, along with practical details on how computational and biological approaches can best be integrated.

This book provides readers with practical computational knowledge and techniques, including programming, and machine learning, enabling them to understand and pursue the immunological aspects of malignancies.

• Presents the knowledge researchers need to apply computational techniques to immunodeficiencies
• Provides the most practical material for bioinformatics approaches to the immunology of cancers
• Gives straightforward and efficient explanations of programming and machine learning approaches in R
• Includes details of the most useful databases, tools, programming packages and algorithms for immunoinformatics
• Illuminates clear explanations with practical examples of immunoinformatic approaches to cancer

About this title

About the Authors

Nima Rezaei, MD, PhD, is Professor of Clinical Immunology and Allergy at Tehran University of Medical Sciences, where he also serves as Associate Dean of International Affairs for the School of Medicine and Director of the Global Academic Program. He is Deputy President of the Research Center for Immunodeficiencies and holds an affiliated research appointment in the Division of Clinical Immunology, Department of Laboratory Medicine, Karolinska Institutet, Sweden. He earned his MD from Tehran University of Medical Sciences and his PhD in Clinical Immunology and Human Genetics from the University of Sheffield, United Kingdom. His research addresses primary immunodeficiencies and translational immunology, with recent work extending into computational and AI-based approaches to immune profiling. He is the founder and President of the Universal Scientific Education and Research Network (USERN) and serves as co-editor of the Springer Nature series Advances in Experimental Medicine and Biology.

Parnian Jabbari is a Medical Doctor at Tehran University of Medical Sciences, and a member of the Network of Immunity in Infection, Malignancy & Autoimmunity (NIIMA). She also works with the Universal Scientific Education & Research Network (USERN), based in Tehran, Iran.

From the Back Cover

The multidisciplinary nature of current research into cancer, assimilating both computation and biological approaches, means that understanding the critical immunological aspects of malignancies, as represented in numerous studies, is a serious challenge. Immunoinformatics of Cancers: Practical Machine Learning Approaches Using R takes a bioinformatics approach to understanding and researching immunological aspects of malignancies, detailing biological and computational principles, and current applications of bioinformatic approaches to the study of human malignancies. Three sections cover the role of immunology in cancers and bioinformatics, including databases and tools; introduce R programming and useful packages; and present the foundations of machine learning, focusing on the most useful algorithms for research and application. The book then gives practical examples to illuminate the application of immunoinformatics to cancer, and practical details on how computational and biological approaches can best be integrated. This title presents key practical computational knowledge and techniques, including programming, and machine learning, helping researchers understand and pursue immunological aspects of malignancies.

Edition details

• Publisher: Academic Press
• Publication date: 2022
• Language: English
• ISBN 10: 0128224002
• ISBN 13: 9780128224007
• Binding: Paperback
• Edition number: 1
• Number of pages: 282