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Cancer Bioinformatics

Overview of attention for book
Cover of 'Cancer Bioinformatics'

Table of Contents

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    Book Overview
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    Chapter 1 A Primer for Access to Repositories of Cancer-Related Genomic Big Data
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    Chapter 2 Building Portable and Reproducible Cancer Informatics Workflows: An RNA Sequencing Case Study
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    Chapter 3 Computational Analysis of Structural Variation in Cancer Genomes
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    Chapter 4 CORE: A Software Tool for Delineating Regions of Recurrent DNA Copy Number Alteration in Cancer
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    Chapter 5 Identification of Mutated Cancer Driver Genes in Unpaired RNA-Seq Samples
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    Chapter 6 A Computational Protocol for Detecting Somatic Mutations by Integrating DNA and RNA Sequencing
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    Chapter 7 Allele-Specific Expression Analysis in Cancer Using Next-Generation Sequencing Data
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    Chapter 8 Computational Analysis of lncRNA Function in Cancer
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    Chapter 9 Computational Methods for Identification of T Cell Neoepitopes in Tumors
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    Chapter 10 Computational and Statistical Analysis of Array-Based DNA Methylation Data
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    Chapter 11 Computational Methods for Subtyping of Tumors and Their Applications for Deciphering Tumor Heterogeneity
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    Chapter 12 Statistically Supported Identification of Tumor Subtypes
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    Chapter 13 Computational Methods for Analysis of Tumor Clonality and Evolutionary History
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    Chapter 14 Predictive Modeling of Anti-Cancer Drug Sensitivity from Genetic Characterizations
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    Chapter 15 In Silico Oncology Drug Repositioning and Polypharmacology
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    Chapter 16 Modeling Growth of Tumors and Their Spreading Behavior Using Mathematical Functions
Overall attention for this book and its chapters
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Mentioned by

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23 tweeters

Citations

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Title
Cancer Bioinformatics
Published by
Springer New York, December 2018
DOI 10.1007/978-1-4939-8868-6
ISBNs
978-1-4939-8866-2, 978-1-4939-8868-6
Editors

Krasnitz, Alexander

Twitter Demographics

The data shown below were collected from the profiles of 23 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 33%
Student > Doctoral Student 1 33%
Student > Bachelor 1 33%
Readers by discipline Count As %
Unspecified 1 33%
Pharmacology, Toxicology and Pharmaceutical Science 1 33%
Biochemistry, Genetics and Molecular Biology 1 33%