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ProKinO: A Unified Resource for Mining the Cancer Kinome
Protein kinases represent a large and diverse family of evolutionarily related proteins that are abnormally regulated in human cancers. Although genome sequencing studies have revealed thousands of variants in protein kinases, translating “big” genomic data into biological knowledge remains a challe...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4342772/ https://www.ncbi.nlm.nih.gov/pubmed/25382819 http://dx.doi.org/10.1002/humu.22726 |
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author | McSkimming, Daniel Ian Dastgheib, Shima Talevich, Eric Narayanan, Anish Katiyar, Samiksha Taylor, Susan S Kochut, Krys Kannan, Natarajan |
author_facet | McSkimming, Daniel Ian Dastgheib, Shima Talevich, Eric Narayanan, Anish Katiyar, Samiksha Taylor, Susan S Kochut, Krys Kannan, Natarajan |
author_sort | McSkimming, Daniel Ian |
collection | PubMed |
description | Protein kinases represent a large and diverse family of evolutionarily related proteins that are abnormally regulated in human cancers. Although genome sequencing studies have revealed thousands of variants in protein kinases, translating “big” genomic data into biological knowledge remains a challenge. Here, we describe an ontological framework for integrating and conceptualizing diverse forms of information related to kinase activation and regulatory mechanisms in a machine readable, human understandable form. We demonstrate the utility of this framework in analyzing the cancer kinome, and in generating testable hypotheses for experimental studies. Through the iterative process of aggregate ontology querying, hypothesis generation and experimental validation, we identify a novel mutational hotspot in the αC-β4 loop of the kinase domain and demonstrate the functional impact of the identified variants in epidermal growth factor receptor (EGFR) constitutive activity and inhibitor sensitivity. We provide a unified resource for the kinase and cancer community, ProKinO, housed at http://vulcan.cs.uga.edu/prokino. |
format | Online Article Text |
id | pubmed-4342772 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-43427722015-03-04 ProKinO: A Unified Resource for Mining the Cancer Kinome McSkimming, Daniel Ian Dastgheib, Shima Talevich, Eric Narayanan, Anish Katiyar, Samiksha Taylor, Susan S Kochut, Krys Kannan, Natarajan Hum Mutat Informatics Protein kinases represent a large and diverse family of evolutionarily related proteins that are abnormally regulated in human cancers. Although genome sequencing studies have revealed thousands of variants in protein kinases, translating “big” genomic data into biological knowledge remains a challenge. Here, we describe an ontological framework for integrating and conceptualizing diverse forms of information related to kinase activation and regulatory mechanisms in a machine readable, human understandable form. We demonstrate the utility of this framework in analyzing the cancer kinome, and in generating testable hypotheses for experimental studies. Through the iterative process of aggregate ontology querying, hypothesis generation and experimental validation, we identify a novel mutational hotspot in the αC-β4 loop of the kinase domain and demonstrate the functional impact of the identified variants in epidermal growth factor receptor (EGFR) constitutive activity and inhibitor sensitivity. We provide a unified resource for the kinase and cancer community, ProKinO, housed at http://vulcan.cs.uga.edu/prokino. Blackwell Publishing Ltd 2015-02 2014-11-10 /pmc/articles/PMC4342772/ /pubmed/25382819 http://dx.doi.org/10.1002/humu.22726 Text en © 2014 The Authors. **Human Mutation published by Wiley Periodicals, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Informatics McSkimming, Daniel Ian Dastgheib, Shima Talevich, Eric Narayanan, Anish Katiyar, Samiksha Taylor, Susan S Kochut, Krys Kannan, Natarajan ProKinO: A Unified Resource for Mining the Cancer Kinome |
title | ProKinO: A Unified Resource for Mining the Cancer Kinome |
title_full | ProKinO: A Unified Resource for Mining the Cancer Kinome |
title_fullStr | ProKinO: A Unified Resource for Mining the Cancer Kinome |
title_full_unstemmed | ProKinO: A Unified Resource for Mining the Cancer Kinome |
title_short | ProKinO: A Unified Resource for Mining the Cancer Kinome |
title_sort | prokino: a unified resource for mining the cancer kinome |
topic | Informatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4342772/ https://www.ncbi.nlm.nih.gov/pubmed/25382819 http://dx.doi.org/10.1002/humu.22726 |
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