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Open AccessArticle

An Optimization-Driven Analysis Pipeline to Uncover Biomarkers and Signaling Paths: Cervix Cancer

Bio IE Lab, The Applied Optimization Group at UPRM, Industrial Engineering Department, University of Puerto Rico at Mayaguez, Call Box 9000, Mayagüez, PR 00681, USA
Pittsburgh Supercomputing Center, 300 S. Craig Street, Pittsburgh, PA 15213, USA
Department of Pharmacology and Toxicology, Ponce School of Medicine, PO Box 700, Ponce, PR 00732, USA
Author to whom correspondence should be addressed.
Academic Editor: Shu-Kay Ng
Microarrays 2015, 4(2), 287-310;
Received: 22 February 2015 / Revised: 27 April 2015 / Accepted: 13 May 2015 / Published: 28 May 2015
(This article belongs to the Special Issue Advanced Methods in Microarrays for Cancer Research)
Establishing how a series of potentially important genes might relate to each other is relevant to understand the origin and evolution of illnesses, such as cancer. High‑throughput biological experiments have played a critical role in providing information in this regard. A special challenge, however, is that of trying to conciliate information from separate microarray experiments to build a potential genetic signaling path. This work proposes a two-step analysis pipeline, based on optimization, to approach meta-analysis aiming to build a proxy for a genetic signaling path. View Full-Text
Keywords: traveling salesman problem; signaling pathways; cancer biology traveling salesman problem; signaling pathways; cancer biology
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Lorenzo, E.; Camacho-Caceres, K.; Ropelewski, A.J.; Rosas, J.; Ortiz-Mojer, M.; Perez-Marty, L.; Irizarry, J.; Gonzalez, V.; Rodríguez, J.A.; Cabrera-Rios, M.; Isaza, C. An Optimization-Driven Analysis Pipeline to Uncover Biomarkers and Signaling Paths: Cervix Cancer. Microarrays 2015, 4, 287-310.

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