Microarrays 2015, 4, 287-310; doi:10.3390/microarrays4020287 OPEN ACCESS microarrays ISSN 2076-3905 www.mdpi.com/journal/microarrays Article An Optimization-Driven Analysis Pipeline to Uncover Biomarkers and Signaling Paths: Cervix Cancer Enery Lorenzo 1, Katia Camacho-Caceres 1, Alexander J. Ropelewski 2, Juan Rosas 1, Michael Ortiz-Mojer 1, Lynn Perez-Marty 1, Juan Irizarry 1, Valerie Gonzalez 1, Jesús A. Rodríguez 1, Mauricio Cabrera-Rios 1 and Clara Isaza 1,3,* 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; E-Mails:
[email protected] (E.L.);
[email protected] (K.C.-C.);
[email protected] (J.R.);
[email protected] (M.O.-M.);
[email protected] (J.I.);
[email protected] (V.G.);
[email protected] (J.A.R.);
[email protected] (M.C.-R.) 2 Pittsburgh Supercomputing Center, 300 S. Craig Street, Pittsburgh, PA 15213, USA; E-Mail:
[email protected] 3 Department of Pharmacology and Toxicology, Ponce School of Medicine, PO Box 700, Ponce, PR 00732, USA * Author to whom correspondence should be addressed; E-Mail:
[email protected]; Tel.: +1-787-840-2575 (ext. 2198). Academic Editor: Shu-Kay Ng Received: 22 February 2015 / Accepted: 13 May 2015 / Published: 28 May 2015 Abstract: 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.