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

Rezaei; Jabbari

 
9780128224007: Immunoinformatics of Cancers: Practical Machine Learning Approaches Using R

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

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About the Authors

Professor Nima Rezaei gained his medical degree (MD) from Tehran University of Medical Sciences and subsequently obtained an MSc in Molecular and Genetic Medicine and a PhD in Clinical Immunology and Human Genetics from the University of Sheffield, UK. He also spent a short-term fellowship of Pediatric Clinical Immunology and Bone Marrow Transplantation in the Newcastle General Hospital. Professor Rezaei is now the Full Professor of Immunology and Vice Dean of Research, School of Medicine, Tehran University of Medical Sciences, and the co-founder and Head of the Research Center for Immunodeficiencies. He is also the founding President of the Universal Scientific Education and Research Network (USERN). Professor Rezaei has already been the Director of more than 55 research projects and has designed and participated in several international collaborative projects. Professor Rezaei is an editorial assistant or board member for more than 30 international journals. He has edited more than 35 international books, has presented more than 500 lectures/posters in congresses/meetings, and has published more than 1,000 scientific papers in the international journals.

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.

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