Statistical application and challenges in global gel-free proteomic analysis by mass spectrometry.

Abstract:

:Global gel-free proteomic analysis by mass spectrometry has been widely used as an important tool for exploring complex biological systems at the whole genome level. Simultaneous analysis of a large number of protein species is a complicated and challenging task. The challenges exist throughout all stages of a global gel-free proteomic analysis: experimental design, peptide/protein identification, data preprocessing and normalization, and inferential analysis. In addition to various efforts to improve the analytical technologies, statistical methodologies have been applied in all stages of proteomic analyses to help extract relevant information efficiently from large proteomic datasets. In this review, we summarize current applications of statistics in several stages of global gel-free proteomic analysis by mass spectrometry. We discuss the challenges associated with the applications of various statistical tools. Whenever possible, we also propose potential solutions on how to improve the data collection and interpretation for mass-spectrometry-based global proteomic analysis using more sophisticated and/or novel statistical approaches.

journal_name

Crit Rev Biotechnol

authors

Nie L,Wu G,Zhang W

doi

10.1080/07388550802543158

subject

Has Abstract

pub_date

2008-01-01 00:00:00

pages

297-307

issue

4

eissn

0738-8551

issn

1549-7801

pii

905979708

journal_volume

28

pub_type

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