Main description:

This volume covers a wide variety of state of the art cancer-related methods and tools for data analysis and interpretation. Chapters were designed to attract a broad readership, ranging from active researchers in computational biology and bioinformatics developers, clinical oncologists, and anti-cancer drug developers wishing to rationalize their search for new compounds. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, installation instructions for computational tools discussed, explanations of the input and output formats, and illustrative examples of applications.

Authoritative and cutting-edge, Cancer Bioinformatics: Methods and Protocols aims to support researchers performing computational analysis of cancer-related data.

Contents:

1. An Access Primer to Repositories of Cancer-related Genomic Big Data

John Torcivia-Rodriguez, Hayley Dingerdissen, Ting-Chia Chang, and Raja Mazumder

2. Building Portable and Reproducible Cancer Informatics Workflows: An RNA Sequencing Case Study

Gaurav Kaushik and Brandi Davis-Dusenbery

3. Computational Analysis of Structural Variation in Cancer Genomes

Matthew Hayes

4. CORE: A Software Tool for Delineating Regions of Recurrent DNA Copy Number Alteration in Cancer

Guoli Sun and Alexander Krasnitz

5. Identification of Mutated Cancer Driver Genes on Unpaired RNA-Seq Samples

David Mosen-Ansorena

6. A Computational Protocol for Detecting Somatic Mutations by Integrating DNA and RNA Sequencing

Matthew D. Wilkerson

7. Allele-specific Expression Analysis in Cancer Using Next Generation Sequencing Data

Alessandro Romanel

8. Computational Analysis of lncRNA Function in Cancer

Xu Zhang and Tsui-Ting Ho

9. Computational Methods for Identification of T Cell Neoepitopes in Tumors

Vanessa Isabell Jurtz and Lars Ronn Olsen

10. Computational and Statistical Analysis of Array-based DNA Methylation Data

Jessica Nordlund, Christofer Backlin, and Amanda Rain

11. Computational Methods for Subtyping Of Tumors and their Applications for Deciphering Tumor Heterogeneity

Shihua Zhang

12. Statistically Supported Identification of Tumor Subtypes

Guoli Sun and Alexander Krasnitz

13. Computational Methods for Analysis of Tumor Clonality and Evolutionary History

Gerald Goh, Nicholas McGranahan and Gareth A. Wilson

14. Predictive Modeling of Anti-cancer Drug Sensitivity from Genetic Characterizations

Raziur Rahman and Ranadip Pal

15. In silico Oncology Drug Repositioning and Polypharmacology

Feixiong Cheng

16. Modelling Growth of Tumours and their Spreading Behaviour using Mathematical Functions

Bertin Hoffmann, Thorsten Frenzel, Rudiger Schmitz, Udo Schumacher , and Gero Wedemann