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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...

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Detalles Bibliográficos
Autores principales: Kim, Yoo-Ah, Cho, Dong-Yeon, Przytycka, Teresa M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
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.
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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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