Functional and genetic analysis of the colon cancer network

Frank Emmert-Streib; Ricardo Simoes de Matos; Galina Glazko; Simon McDade; Benjamin Haibe-Kanis; Andreas Holzinger; Matthias Dehmer; Frederick Charles Campbell

doi:10.1186/1471-2105-15-S6-S6

Functional and genetic analysis of the colon cancer network

Frank Emmert-Streib^*, Ricardo Simoes de Matos, Galina Glazko, Simon McDade, Benjamin Haibe-Kanis, Andreas Holzinger, Matthias Dehmer, Frederick Charles Campbell

^*Corresponding author for this work

Institute of Interactive Systems and Data Science (7060)

Research output: Contribution to journal › Article › peer-review

Abstract

Cancer is a complex disease that has proven to be difficult to understand on the single-gene level. For this reason a functional elucidation needs to take interactions among genes on a systems-level into account. In this study, we infer a colon cancer network from a large-scale gene expression data set by using the method BC3Net. We provide a structural and a functional analysis of this network and also connect its molecular interaction structure with the chromosomal locations of the genes enabling the definition of cis- and trans-interactions. Furthermore, we investigate the interaction of genes that can be found in close neighborhoods on the chromosomes to gain insight into regulatory mechanisms. To our knowledge this is the first study analyzing the genome-scale colon cancer network.

Original language	English
Pages (from-to)	1-15
Journal	BMC Bioinformatics
Volume	15
Issue number	S6
DOIs	https://doi.org/10.1186/1471-2105-15-S6-S6
Publication status	Published - 2014

Keywords

Cancer research
Health Informatics
Data Science
Network Science
Graph-Based Data Mining

ASJC Scopus subject areas

Information Systems

Fields of Expertise

Human- & Biotechnology

Treatment code (Nähere Zuordnung)

Basic - Fundamental (Grundlagenforschung)

UN SDGs

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

Access to Document

10.1186/1471-2105-15-S6-S6Licence: CC BY-ND 4.0

Cite this

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title = "Functional and genetic analysis of the colon cancer network",

abstract = "Cancer is a complex disease that has proven to be difficult to understand on the single-gene level. For this reason a functional elucidation needs to take interactions among genes on a systems-level into account. In this study, we infer a colon cancer network from a large-scale gene expression data set by using the method BC3Net. We provide a structural and a functional analysis of this network and also connect its molecular interaction structure with the chromosomal locations of the genes enabling the definition of cis- and trans-interactions. Furthermore, we investigate the interaction of genes that can be found in close neighborhoods on the chromosomes to gain insight into regulatory mechanisms. To our knowledge this is the first study analyzing the genome-scale colon cancer network.",

keywords = "Cancer research, Health Informatics, Data Science, Network Science, Graph-Based Data Mining",

author = "Frank Emmert-Streib and {Simoes de Matos}, Ricardo and Galina Glazko and Simon McDade and Benjamin Haibe-Kanis and Andreas Holzinger and Matthias Dehmer and Campbell, {Frederick Charles}",

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doi = "10.1186/1471-2105-15-S6-S6",

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T1 - Functional and genetic analysis of the colon cancer network

AU - Emmert-Streib, Frank

AU - Simoes de Matos, Ricardo

AU - Glazko, Galina

AU - McDade, Simon

AU - Haibe-Kanis, Benjamin

AU - Holzinger, Andreas

AU - Dehmer, Matthias

AU - Campbell, Frederick Charles

PY - 2014

Y1 - 2014

N2 - Cancer is a complex disease that has proven to be difficult to understand on the single-gene level. For this reason a functional elucidation needs to take interactions among genes on a systems-level into account. In this study, we infer a colon cancer network from a large-scale gene expression data set by using the method BC3Net. We provide a structural and a functional analysis of this network and also connect its molecular interaction structure with the chromosomal locations of the genes enabling the definition of cis- and trans-interactions. Furthermore, we investigate the interaction of genes that can be found in close neighborhoods on the chromosomes to gain insight into regulatory mechanisms. To our knowledge this is the first study analyzing the genome-scale colon cancer network.

AB - Cancer is a complex disease that has proven to be difficult to understand on the single-gene level. For this reason a functional elucidation needs to take interactions among genes on a systems-level into account. In this study, we infer a colon cancer network from a large-scale gene expression data set by using the method BC3Net. We provide a structural and a functional analysis of this network and also connect its molecular interaction structure with the chromosomal locations of the genes enabling the definition of cis- and trans-interactions. Furthermore, we investigate the interaction of genes that can be found in close neighborhoods on the chromosomes to gain insight into regulatory mechanisms. To our knowledge this is the first study analyzing the genome-scale colon cancer network.

KW - Cancer research

KW - Health Informatics

KW - Data Science

KW - Network Science

KW - Graph-Based Data Mining

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U2 - 10.1186/1471-2105-15-S6-S6

DO - 10.1186/1471-2105-15-S6-S6

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JO - BMC Bioinformatics

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Functional and genetic analysis of the colon cancer network

Abstract

Keywords

ASJC Scopus subject areas

Fields of Expertise

Treatment code (Nähere Zuordnung)

UN SDGs

Access to Document

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