viernes, 25 de febrero de 2011

A novel network model identified a 13-gene lung ca... [Int J Comput Biol Drug Des. 2011] - PubMed result



Int J Comput Biol Drug Des. 2011;4(1):19-39. doi: 10.1504/IJCBDD.2011.038655. Epub 2011 Feb 17.

A novel network model identified a 13-gene lung cancer prognostic signature.
Guo NL, Wan YW, Bose S, Denvir J, Kashon ML, Andrew ME.

Mary Babb Randolph Cancer Centre, Department of Community Medicine, West Virginia University, Morgantown, WV 26506 – 9300, USA.



Abstract

This study presents a novel network methodology to identify prognostic gene signatures. Implication networks based on prediction logic are used to construct genome-wide coexpression networks for different disease states. From the differential components associated with specific disease states, candidate genes that are co-expressed with major disease signal hallmarks are selected. From these candidate genes, top genes that are the most predictive of clinical outcome are identified using univariate Cox model and Relief algorithm. Using this approach, a 13-gene lung cancer prognosis signature was identified, which generated significant prognostic stratifications (log-rank P < 0.05) in Director's Challenge Study (n = 442).

PMID: 21330692 [PubMed - in process]

A novel network model identified a 13-gene lung ca... [Int J Comput Biol Drug Des. 2011] - PubMed result

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