Literature DB >> 15234244

Bioinformatics strategies for proteomic profiling.

C Nicole White1, Daniel W Chan, Zhen Zhang.   

Abstract

Clinical proteomics is an emerging field that involves the analysis of protein expression profiles of clinical samples for de novo discovery of disease-associated biomarkers and for gaining insight into the biology of disease processes. Mass spectrometry represents an important set of technologies for protein expression measurement. Among them, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS), because of its high throughput and on-chip sample processing capability, has become a popular tool for clinical proteomics. Bioinformatics plays a critical role in the analysis of SELDI data, and therefore, it is important to understand the issues associated with the analysis of clinical proteomic data. In this review, we discuss such issues and the bioinformatics strategies used for proteomic profiling.

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Year:  2004        PMID: 15234244     DOI: 10.1016/j.clinbiochem.2004.05.004

Source DB:  PubMed          Journal:  Clin Biochem        ISSN: 0009-9120            Impact factor:   3.281


  7 in total

1.  Clinical proteomics: present and future prospects.

Authors:  Nicole M Verrills
Journal:  Clin Biochem Rev       Date:  2006-05

Review 2.  Contribution of oncoproteomics to cancer biomarker discovery.

Authors:  William C S Cho
Journal:  Mol Cancer       Date:  2007-04-02       Impact factor: 27.401

3.  Integrated multi-level quality control for proteomic profiling studies using mass spectrometry.

Authors:  David A Cairns; David N Perkins; Anthea J Stanley; Douglas Thompson; Jennifer H Barrett; Peter J Selby; Rosamonde E Banks
Journal:  BMC Bioinformatics       Date:  2008-12-04       Impact factor: 3.169

4.  Laboratory methods to improve SELDI peak detection and quantitation.

Authors:  Dominique Rollin; Toni Whistler; Suzanne D Vernon
Journal:  Proteome Sci       Date:  2007-07-02       Impact factor: 2.480

5.  A method for improving SELDI-TOF mass spectrometry data quality.

Authors:  Toni Whistler; Dominique Rollin; Suzanne D Vernon
Journal:  Proteome Sci       Date:  2007-09-05       Impact factor: 2.480

6.  Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles.

Authors:  Guangtao Ge; G William Wong
Journal:  BMC Bioinformatics       Date:  2008-06-11       Impact factor: 3.169

7.  Neuroproteome changes after ischemia/reperfusion injury and tissue plasminogen activator administration in rats: a quantitative iTRAQ proteomics study.

Authors:  Zamir Merali; Meah MingYang Gao; Tim Bowes; Jian Chen; Kenneth Evans; Andrea Kassner
Journal:  PLoS One       Date:  2014-05-30       Impact factor: 3.240

  7 in total

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