title: Translational bioinformatics for diagnostic and prognostic prediction of prostate cancer in the next-generation sequencing era.
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.
authors: Center for Systems Biology, Soochow University, Suzhou 215006, China.
authors: Jiajia
authors: J
authors: Chen
authors: Daqing
authors: D
authors: Zhang
authors: Wenying
authors: W
authors: Yan
authors: Dongrong
authors: D
authors: Yang
authors: Bairong
authors: B
authors: Shen
mesh_terms: D019295:Computational Biology / Q000379:methods*; D015894:Genome, Human; D023281:Genomics; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008297:Male; D011379:Prognosis; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000473:pathology; D014176:Protein Biosynthesis
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