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Int. J. Mol. Sci. 2016, 17(2), 191; doi:10.3390/ijms17020191

Prioritization of Susceptibility Genes for Ectopic Pregnancy by Gene Network Analysis

College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China
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Author to whom correspondence should be addressed.
Academic Editor: Nicholas Delihas
Received: 14 December 2015 / Revised: 14 January 2016 / Accepted: 27 January 2016 / Published: 1 February 2016
(This article belongs to the Section Biochemistry, Molecular and Cellular Biology)
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Abstract

Ectopic pregnancy is a very dangerous complication of pregnancy, affecting 1%–2% of all reported pregnancies. Due to ethical constraints on human biopsies and the lack of suitable animal models, there has been little success in identifying functionally important genes in the pathogenesis of ectopic pregnancy. In the present study, we developed a random walk–based computational method named TM-rank to prioritize ectopic pregnancy–related genes based on text mining data and gene network information. Using a defined threshold value, we identified five top-ranked genes: VEGFA (vascular endothelial growth factor A), IL8 (interleukin 8), IL6 (interleukin 6), ESR1 (estrogen receptor 1) and EGFR (epidermal growth factor receptor). These genes are promising candidate genes that can serve as useful diagnostic biomarkers and therapeutic targets. Our approach represents a novel strategy for prioritizing disease susceptibility genes. View Full-Text
Keywords: ectopic pregnancy; pathogenesis; text mining; gene prioritization ectopic pregnancy; pathogenesis; text mining; gene prioritization
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Liu, J.-L.; Zhao, M. Prioritization of Susceptibility Genes for Ectopic Pregnancy by Gene Network Analysis. Int. J. Mol. Sci. 2016, 17, 191.

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