Immunoinformatics of Cancers
Practical Machine Learning Approaches Using R

Presents practical, computational knowledge and techniques available in bioinformatics, programming and machine learning in R for research on the immunological aspects of malignancies

Nima Rezaei (Author), Parnian Jabbari (Author)

9780128224007, Elsevier Science

Paperback, published 21 April 2022

282 pages
22.9 x 15.2 x 1.9 cm, 0.43 kg

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.

Section I
1. Introduciton to cancer immunology
2. Introduction to bioinformatics
3. Practical databases in immunoinformatics

Section II
4. Principles of R programming
5. R programming in bioinformatics
6. Principle R packages in immunoinformatics

Section III
7. Introduction to machine learning
8. Naïve Bayes in R
9. Regressions in R
10. Linear and quadratic discriminant analysis
11. Support-vector Machine in R
12. Decision trees in R
13. Random forests in R
14. Neural Network in R
15. K Nearest Neighbour in R
16. Practice examples

Subject Areas: Immunology [MJCM]