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 Rønn Olsen
10. Computational and Statistical Analysis of Array-based DNA Methylation Data
Jessica Nordlund, Christofer Bäcklin, 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, Rüdiger Schmitz, Udo Schumacher, and Gero Wedemann
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.
