Cargando…

Exploring cancer genomic data from the cancer genome atlas project

The Cancer Genome Atlas (TCGA) has compiled genomic, epigenomic, and proteomic data from more than 10,000 samples derived from 33 types of cancer, aiming to improve our understanding of the molecular basis of cancer development. Availability of these genome-wide information provides an unprecedented...

Descripción completa

Detalles Bibliográficos
Autor principal: Lee, Ju-Seog
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society for Biochemistry and Molecular Biology 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5346320/
https://www.ncbi.nlm.nih.gov/pubmed/27530686
http://dx.doi.org/10.5483/BMBRep.2016.49.11.145
_version_ 1782513864309473280
author Lee, Ju-Seog
author_facet Lee, Ju-Seog
author_sort Lee, Ju-Seog
collection PubMed
description The Cancer Genome Atlas (TCGA) has compiled genomic, epigenomic, and proteomic data from more than 10,000 samples derived from 33 types of cancer, aiming to improve our understanding of the molecular basis of cancer development. Availability of these genome-wide information provides an unprecedented opportunity for uncovering new key regulators of signaling pathways or new roles of pre-existing members in pathways. To take advantage of the advancement, it will be necessary to learn systematic approaches that can help to uncover novel genes reflecting genetic alterations, prognosis, or response to treatments. This minireview describes the updated status of TCGA project and explains how to use TCGA data.
format Online
Article
Text
id pubmed-5346320
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Korean Society for Biochemistry and Molecular Biology
record_format MEDLINE/PubMed
spelling pubmed-53463202017-04-06 Exploring cancer genomic data from the cancer genome atlas project Lee, Ju-Seog BMB Rep Invited Mini Review The Cancer Genome Atlas (TCGA) has compiled genomic, epigenomic, and proteomic data from more than 10,000 samples derived from 33 types of cancer, aiming to improve our understanding of the molecular basis of cancer development. Availability of these genome-wide information provides an unprecedented opportunity for uncovering new key regulators of signaling pathways or new roles of pre-existing members in pathways. To take advantage of the advancement, it will be necessary to learn systematic approaches that can help to uncover novel genes reflecting genetic alterations, prognosis, or response to treatments. This minireview describes the updated status of TCGA project and explains how to use TCGA data. Korean Society for Biochemistry and Molecular Biology 2016 2016-11-30 /pmc/articles/PMC5346320/ /pubmed/27530686 http://dx.doi.org/10.5483/BMBRep.2016.49.11.145 Text en Copyright © 2016 by the The Korean Society for Biochemistry and Molecular Biology http://creativecommons.org/licenses/by-nc/4.0 This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Invited Mini Review
Lee, Ju-Seog
Exploring cancer genomic data from the cancer genome atlas project
title Exploring cancer genomic data from the cancer genome atlas project
title_full Exploring cancer genomic data from the cancer genome atlas project
title_fullStr Exploring cancer genomic data from the cancer genome atlas project
title_full_unstemmed Exploring cancer genomic data from the cancer genome atlas project
title_short Exploring cancer genomic data from the cancer genome atlas project
title_sort exploring cancer genomic data from the cancer genome atlas project
topic Invited Mini Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5346320/
https://www.ncbi.nlm.nih.gov/pubmed/27530686
http://dx.doi.org/10.5483/BMBRep.2016.49.11.145
work_keys_str_mv AT leejuseog exploringcancergenomicdatafromthecancergenomeatlasproject