Overview of Public Cancer Databases, Resources, and Visualization Tools

Frank Emmert-Streib; Ricardo De Matos Simoes; Shailesh Tripathi; Matthias Dehmer

doi:10.1002/9783527665471.ch2

Overview of Public Cancer Databases, Resources, and Visualization Tools

Frank Emmert-Streib^*
, Ricardo De Matos Simoes
, Shailesh Tripathi
, Matthias Dehmer

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Scientific › peer-review

Abstract

In this chapter, we provide a general overview of incidence and mortality rates of the most severe cancer types. Further, we provide information about public databases containing valuable resources, for example, expression data or SNP arrays. Due to the complex nature of cancer, we do not limit ourselves to just one cancer type but provide information about a large variety of different cancer types. As motivation for this, we briefly review the Human Disease Network [1,2] focusing on a subnetwork thereof showing a network consisting of different cancer types. Finally, we advocate the usage of the statistical programming language R as a flexible and efficient means to integrate the multilevel sources from different databases with each other.

Original language	English
Title of host publication	Statistical Diagnostics for Cancer: Analyzing High-Dimensional Data
Publisher	Wiley-VCH Verlag
Pages	27-40
Number of pages	14
Volume	3
ISBN (Print)	9783527332625
DOIs	https://doi.org/10.1002/9783527665471.ch2
Publication status	Published - 8 Apr 2013
Publication type	A3 Book chapter

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Genetic cancer network
Human disease network
Lung cancer
Methylation
Next-generation sequencing (NGS)
Protein-protein interactions

ASJC Scopus subject areas

General Biochemistry,Genetics and Molecular Biology

Access to Document

10.1002/9783527665471.ch2

Cite this

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abstract = "In this chapter, we provide a general overview of incidence and mortality rates of the most severe cancer types. Further, we provide information about public databases containing valuable resources, for example, expression data or SNP arrays. Due to the complex nature of cancer, we do not limit ourselves to just one cancer type but provide information about a large variety of different cancer types. As motivation for this, we briefly review the Human Disease Network [1,2] focusing on a subnetwork thereof showing a network consisting of different cancer types. Finally, we advocate the usage of the statistical programming language R as a flexible and efficient means to integrate the multilevel sources from different databases with each other.",

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year = "2013",

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doi = "10.1002/9783527665471.ch2",

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AU - De Matos Simoes, Ricardo

AU - Tripathi, Shailesh

AU - Dehmer, Matthias

PY - 2013/4/8

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KW - Human disease network

KW - Lung cancer

KW - Methylation

KW - Next-generation sequencing (NGS)

KW - Protein-protein interactions

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M3 - Chapter

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BT - Statistical Diagnostics for Cancer: Analyzing High-Dimensional Data

PB - Wiley-VCH Verlag

ER -

Overview of Public Cancer Databases, Resources, and Visualization Tools

Abstract

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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