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Bioinformatics challenges for personalized medicine

Motivation: Widespread availability of low-cost, full genome sequencing will introduce new challenges for bioinformatics. Results: This review outlines recent developments in sequencing technologies and genome analysis methods for application in personalized medicine. New methods are needed in four...

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Detalles Bibliográficos
Autores principales: Fernald, Guy Haskin, Capriotti, Emidio, Daneshjou, Roxana, Karczewski, Konrad J., Altman, Russ B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117361/
https://www.ncbi.nlm.nih.gov/pubmed/21596790
http://dx.doi.org/10.1093/bioinformatics/btr295
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author Fernald, Guy Haskin
Capriotti, Emidio
Daneshjou, Roxana
Karczewski, Konrad J.
Altman, Russ B.
author_facet Fernald, Guy Haskin
Capriotti, Emidio
Daneshjou, Roxana
Karczewski, Konrad J.
Altman, Russ B.
author_sort Fernald, Guy Haskin
collection PubMed
description Motivation: Widespread availability of low-cost, full genome sequencing will introduce new challenges for bioinformatics. Results: This review outlines recent developments in sequencing technologies and genome analysis methods for application in personalized medicine. New methods are needed in four areas to realize the potential of personalized medicine: (i) processing large-scale robust genomic data; (ii) interpreting the functional effect and the impact of genomic variation; (iii) integrating systems data to relate complex genetic interactions with phenotypes; and (iv) translating these discoveries into medical practice. Contact: russ.altman@stanford.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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spelling pubmed-31173612011-06-17 Bioinformatics challenges for personalized medicine Fernald, Guy Haskin Capriotti, Emidio Daneshjou, Roxana Karczewski, Konrad J. Altman, Russ B. Bioinformatics Review Motivation: Widespread availability of low-cost, full genome sequencing will introduce new challenges for bioinformatics. Results: This review outlines recent developments in sequencing technologies and genome analysis methods for application in personalized medicine. New methods are needed in four areas to realize the potential of personalized medicine: (i) processing large-scale robust genomic data; (ii) interpreting the functional effect and the impact of genomic variation; (iii) integrating systems data to relate complex genetic interactions with phenotypes; and (iv) translating these discoveries into medical practice. Contact: russ.altman@stanford.edu Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2011-07-01 2011-05-19 /pmc/articles/PMC3117361/ /pubmed/21596790 http://dx.doi.org/10.1093/bioinformatics/btr295 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Fernald, Guy Haskin
Capriotti, Emidio
Daneshjou, Roxana
Karczewski, Konrad J.
Altman, Russ B.
Bioinformatics challenges for personalized medicine
title Bioinformatics challenges for personalized medicine
title_full Bioinformatics challenges for personalized medicine
title_fullStr Bioinformatics challenges for personalized medicine
title_full_unstemmed Bioinformatics challenges for personalized medicine
title_short Bioinformatics challenges for personalized medicine
title_sort bioinformatics challenges for personalized medicine
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117361/
https://www.ncbi.nlm.nih.gov/pubmed/21596790
http://dx.doi.org/10.1093/bioinformatics/btr295
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