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

被引：24

作者：

Chen, Jiajia ^{[1
,2
]}

Zhang, Daqing ^{[1
]}

Yan, Wenying ^{[1
]}

Yang, Dongrong ^{[3
]}

Shen, Bairong ^{[1
]}

机构：

[1] Soochow Univ, Ctr Syst Biol, Suzhou 215006, Peoples R China

[2] Suzhou Univ Sci & Technol, Sch Chem Biol & Mat Engn, Suzhou 215011, Peoples R China

[3] Soochow Univ, Dept Urol, Affiliated Hosp 2, Suzhou 215004, Peoples R China

来源：

BIOMED RESEARCH INTERNATIONAL | 2013年 / 2013卷

基金：

中国国家自然科学基金; 高等学校博士学科点专项科研基金; 国家高技术研究发展计划(863计划);

关键词：

GENE FUSIONS; SOLUBLE RECEPTOR; PLASMA-LEVELS; COPY NUMBER; GENOMIC ALTERATIONS; DNA METHYLATION; EXPRESSION; PROGRESSION; REVEALS; MUTATIONS;

D O I：

10.1155/2013/901578

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

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.

引用

页数：13

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