Journal article
Integrative network-based Bayesian analysis of diverse genomics data
- Abstract:
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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.
Expand abstract
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...
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Version of record, pdf, 1.8MB)
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- Publisher copy:
- 10.1186/1471-2105-14-s13-s8
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Authors
Bibliographic Details
- Publisher:
- BioMed Central Publisher's website
- Journal:
- BMC Bioinformatics Journal website
- Volume:
- 14
- Article number:
- S8
- Publication date:
- 2013-10-01
- DOI:
- EISSN:
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1471-2105
- Source identifiers:
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439789
Item Description
- Language:
- English
- Keywords:
- UUID:
-
uuid:4b2198a2-b6d8-44b9-bf68-fdd1e61d3d87
- Local pid:
- pubs:439789
- Deposit date:
- 2014-10-15
Terms of use
- Copyright holder:
- Wang et al
- Copyright date:
- 2013
- Notes:
- © 2013 Wang et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Licence:
- CC Attribution (CC BY)
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