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Bioinformatics strategies for proteomic profiling.

C Nicole White·Daniel W Chan·Zhen Zhang
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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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Computational BiologyGene Expression ProfilingHumansMass SpectrometryProteomicsQuality ControlSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, P.H.S.Review

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C Nicole White, Daniel W Chan, Zhen Zhang. 2004. Bioinformatics strategies for proteomic profiling.. https://doi.org/10.1016/j.clinbiochem.2004.05.004

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