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Open AccessArticle

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

1
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
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Pittsburgh Supercomputing Center, 300 S. Craig Street, Pittsburgh, PA 15213, USA
3
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; https://doi.org/10.3390/microarrays4020287
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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