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

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 revi...

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Publicado en:BioMed Research International Vol. 2013; pp. 901578 - 901579
Autores principales: Chen, Jiajia, Zhang, Daqing, Yan, Wenying, Yang, Dongrong, Shen, Bairong
Formato: Journal Article
Publicado: Wiley-Blackwell 2013
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Translational bioinformatics for diagnostic and prognostic prediction of prostate cancer in the next-generation sequencing era.
      aug:
        au:
          Chen, Jiajia
          Zhang, Daqing
          Yan, Wenying
          Yang, Dongrong
          Shen, Bairong
        affil: 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.
      sug:
        subj:
          Bioinformatics Methods
          Sequence Analysis
          Prostatic Neoplasms
          Proteins
          Genome, Human
          Genomics
          Male
          Prognosis
          Prostatic Neoplasms Diagnosis
          Prostatic Neoplasms Pathology
          Male
      ab: 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.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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