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Understanding Genotype-Phenotype Effects in Cancer via Network Approaches
Cancer is now increasingly studied from the perspective of dysregulated pathways, rather than as a disease resulting from mutations of individual genes. A pathway-centric view acknowledges the heterogeneity between genomic profiles from different cancer patients while assuming that the mutated genes...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4786343/ https://www.ncbi.nlm.nih.gov/pubmed/26963104 http://dx.doi.org/10.1371/journal.pcbi.1004747 |
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author | Kim, Yoo-Ah Cho, Dong-Yeon Przytycka, Teresa M. |
author_facet | Kim, Yoo-Ah Cho, Dong-Yeon Przytycka, Teresa M. |
author_sort | Kim, Yoo-Ah |
collection | PubMed |
description | Cancer is now increasingly studied from the perspective of dysregulated pathways, rather than as a disease resulting from mutations of individual genes. A pathway-centric view acknowledges the heterogeneity between genomic profiles from different cancer patients while assuming that the mutated genes are likely to belong to the same pathway and cause similar disease phenotypes. Indeed, network-centric approaches have proven to be helpful for finding genotypic causes of diseases, classifying disease subtypes, and identifying drug targets. In this review, we discuss how networks can be used to help understand patient-to-patient variations and how one can leverage this variability to elucidate interactions between cancer drivers. |
format | Online Article Text |
id | pubmed-4786343 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-47863432016-03-23 Understanding Genotype-Phenotype Effects in Cancer via Network Approaches Kim, Yoo-Ah Cho, Dong-Yeon Przytycka, Teresa M. PLoS Comput Biol Perspective Cancer is now increasingly studied from the perspective of dysregulated pathways, rather than as a disease resulting from mutations of individual genes. A pathway-centric view acknowledges the heterogeneity between genomic profiles from different cancer patients while assuming that the mutated genes are likely to belong to the same pathway and cause similar disease phenotypes. Indeed, network-centric approaches have proven to be helpful for finding genotypic causes of diseases, classifying disease subtypes, and identifying drug targets. In this review, we discuss how networks can be used to help understand patient-to-patient variations and how one can leverage this variability to elucidate interactions between cancer drivers. Public Library of Science 2016-03-10 /pmc/articles/PMC4786343/ /pubmed/26963104 http://dx.doi.org/10.1371/journal.pcbi.1004747 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Perspective Kim, Yoo-Ah Cho, Dong-Yeon Przytycka, Teresa M. Understanding Genotype-Phenotype Effects in Cancer via Network Approaches |
title | Understanding Genotype-Phenotype Effects in Cancer via Network Approaches |
title_full | Understanding Genotype-Phenotype Effects in Cancer via Network Approaches |
title_fullStr | Understanding Genotype-Phenotype Effects in Cancer via Network Approaches |
title_full_unstemmed | Understanding Genotype-Phenotype Effects in Cancer via Network Approaches |
title_short | Understanding Genotype-Phenotype Effects in Cancer via Network Approaches |
title_sort | understanding genotype-phenotype effects in cancer via network approaches |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4786343/ https://www.ncbi.nlm.nih.gov/pubmed/26963104 http://dx.doi.org/10.1371/journal.pcbi.1004747 |
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