iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data

Motivation: Analyzing data from multi-platform genomics experiments combined with patients’ clinical outcomes helps us understand the complex biological processes that characterize a disease, as well as how these processes relate to the development of the disease. Current data integration approaches...

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Main Authors:	Wang, Wenting, Baladandayuthapani, Veerabhadran, Morris, Jeffrey S., Broom, Bradley M., Manyam, Ganiraju, Do, Kim-Anh
Format:	Online
Language:	English
Published:	Oxford University Press 2013
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546799/

id	pubmed-3546799
recordtype	oai_dc
spelling	pubmed-35467992013-01-16 iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data Wang, Wenting Baladandayuthapani, Veerabhadran Morris, Jeffrey S. Broom, Bradley M. Manyam, Ganiraju Do, Kim-Anh Original Papers Motivation: Analyzing data from multi-platform genomics experiments combined with patients’ clinical outcomes helps us understand the complex biological processes that characterize a disease, as well as how these processes relate to the development of the disease. Current data integration approaches are limited in that they do not consider the fundamental biological relationships that exist among the data obtained from different platforms. Oxford University Press 2013-01-15 2012-11-09 /pmc/articles/PMC3546799/ /pubmed/23142963 http://dx.doi.org/10.1093/bioinformatics/bts655 Text en © The Author 2012. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Wang, Wenting Baladandayuthapani, Veerabhadran Morris, Jeffrey S. Broom, Bradley M. Manyam, Ganiraju Do, Kim-Anh
spellingShingle	Wang, Wenting Baladandayuthapani, Veerabhadran Morris, Jeffrey S. Broom, Bradley M. Manyam, Ganiraju Do, Kim-Anh iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data
author_facet	Wang, Wenting Baladandayuthapani, Veerabhadran Morris, Jeffrey S. Broom, Bradley M. Manyam, Ganiraju Do, Kim-Anh
author_sort	Wang, Wenting
title	iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data
title_short	iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data
title_full	iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data
title_fullStr	iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data
title_full_unstemmed	iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data
title_sort	ibag: integrative bayesian analysis of high-dimensional multiplatform genomics data
description	Motivation: Analyzing data from multi-platform genomics experiments combined with patients’ clinical outcomes helps us understand the complex biological processes that characterize a disease, as well as how these processes relate to the development of the disease. Current data integration approaches are limited in that they do not consider the fundamental biological relationships that exist among the data obtained from different platforms.
publisher	Oxford University Press
publishDate	2013
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546799/
_version_	1611947540725366784

iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data

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