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Bioinformatics strategies for proteomic profiling.

C Nicole White1, Daniel W Chan, Zhen Zhang

  • 1Department of Pathology, Johns Hopkins Medical Institutions, Baltimore, MD 21231, USA. cnwhite@jhu.edu

Clinical Biochemistry
|July 6, 2004
PubMed
Summary
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This review covers clinical proteomics, focusing on surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS) for biomarker discovery. It highlights bioinformatics challenges and strategies for analyzing SELDI proteomic data.

Area of Science:

  • Proteomics
  • Biotechnology
  • Bioinformatics

Background:

  • Clinical proteomics analyzes protein expression in samples to find disease biomarkers and understand disease biology.
  • Mass spectrometry is key for protein expression measurement in clinical proteomics.
  • Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS) is popular due to its high throughput and on-chip sample processing.

Purpose of the Study:

  • To discuss challenges in analyzing clinical proteomic data, particularly from SELDI TOF-MS.
  • To review bioinformatics strategies essential for effective proteomic profiling.

Main Methods:

  • Review of existing literature on clinical proteomics and SELDI TOF-MS data analysis.
  • Discussion of bioinformatics tools and approaches for handling proteomic datasets.

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Main Results:

  • Identification of critical issues in clinical proteomic data analysis.
  • Overview of various bioinformatics strategies applicable to SELDI TOF-MS data.

Conclusions:

  • Bioinformatics is crucial for interpreting complex clinical proteomic data.
  • Understanding these bioinformatics challenges is vital for advancing disease biomarker discovery.