Translational bioinformatics for diagnostic and prognostic prediction of prostate cancer in the next-generation sequencing era

48Citations
Citations of this article
136Readers
Mendeley users who have this article in their library.

This article is free to access.

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. © 2013 Jiajia Chen et al.

Cite

CITATION STYLE

APA

Chen, J., Zhang, D., Yan, W., Yang, D., & Shen, B. (2013). Translational bioinformatics for diagnostic and prognostic prediction of prostate cancer in the next-generation sequencing era. BioMed Research International. https://doi.org/10.1155/2013/901578

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free