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Integrative network-based Bayesian analysis of diverse genomics data

Abstract:

Background: In order to better understand cancer as a complex disease with multiple genetic and epigenetic factors, it is vital to model the fundamental biological relationships among these alterations as well as their relationships with important clinical outcomes.

Methods: We develop an i ntegrative net work-based Bayesian analysis (iNET) approach that allows us to jointly analyze multi-platform high-dimensional genomic data in a comp...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1186/1471-2105-14-s13-s8

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Institution:
University of Oxford
Division:
MSD
Department:
NDM
Role:
Author
Publisher:
BioMed Central Publisher's website
Journal:
BMC Bioinformatics Journal website
Volume:
14
Article number:
S8
Publication date:
2013-10-01
DOI:
EISSN:
1471-2105
Source identifiers:
439789
Language:
English
Keywords:
UUID:
uuid:4b2198a2-b6d8-44b9-bf68-fdd1e61d3d87
Local pid:
pubs:439789
Deposit date:
2014-10-15

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