Computational proteomics: designing a comprehensive analytical strategy

被引：12

作者：

Bin Goh, Wilson Wen ^{[1
,2
]}

Wong, Limsoon ^{[1
]}

机构：

[1] Natl Univ Singapore, Dept Comp Sci, Singapore 117417, Singapore

[2] Univ London Imperial Coll Sci Technol & Med, Dept Comp, London SW7 2AZ, England

来源：

DRUG DISCOVERY TODAY | 2014年 / 19卷 / 03期

基金：

英国惠康基金;

关键词：

TANDEM MASS-SPECTROMETRY; CANCER TISSUE SAMPLES; GENE ONTOLOGY TERMS; PROTEIN IDENTIFICATION; SHOTGUN PROTEOMICS; SOFTWARE; PREDICTION; QUANTIFICATION; GENERATION; ALGORITHM;

D O I：

10.1016/j.drudis.2013.07.008

中图分类号：

R9 [药学];

学科分类号：

100702 [药剂学];

摘要：

The proper combination of proteomics with bioinformatics is highly synergistic, capable of propelling proteomics into a truly high-throughput platform. However, appropriate experimental design and analytical considerations are needed to maximize analytical outcome. This review highlights key issues and caveats in converting raw data to protein identifications, and subsequently biological insight. It offers some insights on how the establishment of highly robust proteomics pipelines can be used for studying novel areas such as computational epigenetics, high performance functional studies and new discovery paradigms for drug targets and biomarkers

引用

页码：266 / 274

页数：9

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