Translational Bioinformatics for Diagnostic and Prognostic Prediction of Prostate Cancer in the Next-Generation Sequencing EraReport as inadecuate




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BioMed Research InternationalVolume 2013 2013, Article ID 901578, 13 pages

Review Article

Center for Systems Biology, Soochow University, Suzhou 215006, China

School of Chemistry, Biology and Material Engineering, Suzhou University of Science and Technology, Suzhou 215011, China

Department of Urology, The Second Affiliated Hospital of Soochow University, Suzhou 215004, China

Received 1 May 2013; Accepted 22 June 2013

Academic Editor: Xinghua Lu

Copyright © 2013 Jiajia Chen et al. 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.

Abstract

The discovery of prostate cancer biomarkers has been boosted by the advent of next-generation sequencing NGS technologies. Nevertheless, many challenges still exist in exploiting the flood of sequence data and translating them into routine diagnostics and prognosis of prostate cancer. Here we review the recent developments in prostate cancer biomarkers by high throughput sequencing technologies. We highlight some fundamental issues of translational bioinformatics and the potential use of cloud computing in NGS data processing for the improvement of prostate cancer treatment.





Author: Jiajia Chen, Daqing Zhang, Wenying Yan, Dongrong Yang, and Bairong Shen

Source: https://www.hindawi.com/



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