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Meta-analysis of Cancer Gene Profiling Data.

Roy, Janine; Winter, Christof LU and Schroeder, Michael (2016) In Methods in Molecular Biology 1381. p.211-222
Abstract
The simultaneous measurement of thousands of genes gives the opportunity to personalize and improve cancer therapy. In addition, the integration of meta-data such as protein-protein interaction (PPI) information into the analyses helps in the identification and prioritization of genes from these screens.Here, we describe a computational approach that identifies genes prognostic for outcome by combining gene profiling data from any source with a network of known relationships between genes.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Methods in Molecular Biology
volume
1381
pages
211 - 222
publisher
Springer
external identifiers
  • pmid:26667463
  • scopus:84949934370
ISSN
1940-6029
DOI
10.1007/978-1-4939-3204-7_12
language
English
LU publication?
yes
id
274f5032-a4dd-42d6-9759-1ac466b9b11c (old id 8504778)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/26667463?dopt=Abstract
date added to LUP
2016-01-12 12:27:08
date last changed
2017-01-01 07:33:24
@article{274f5032-a4dd-42d6-9759-1ac466b9b11c,
  abstract     = {The simultaneous measurement of thousands of genes gives the opportunity to personalize and improve cancer therapy. In addition, the integration of meta-data such as protein-protein interaction (PPI) information into the analyses helps in the identification and prioritization of genes from these screens.Here, we describe a computational approach that identifies genes prognostic for outcome by combining gene profiling data from any source with a network of known relationships between genes.},
  author       = {Roy, Janine and Winter, Christof and Schroeder, Michael},
  issn         = {1940-6029},
  language     = {eng},
  pages        = {211--222},
  publisher    = {Springer},
  series       = {Methods in Molecular Biology},
  title        = {Meta-analysis of Cancer Gene Profiling Data.},
  url          = {http://dx.doi.org/10.1007/978-1-4939-3204-7_12},
  volume       = {1381},
  year         = {2016},
}