Pharmaceutical Sciences Faculty Publications

Title

Analysis of Mass Spectral Serum Profiles for Biomarker Selection

Document Type

Article

Publication Date

9-13-2005

Journal Title

Bioinformatics

Volume

21

Issue

21

First Page

4039

Last Page

4045

DOI

10.1093/bioinformatics/bti670

Abstract

Motivation: Mass spectrometric profiles of peptides and proteins obtained by current technologies are characterized by complex spectra, high dimensionality and substantial noise. These characteristics generate challenges in the discovery of proteins and protein-profiles that distinguish disease states, e.g. cancer patients from healthy individuals. We present low-level methods for the processing of mass spectral data and a machine learning method that combines support vector machines, with particle swarm optimization for biomarker selection.

Results: The proposed method identified mass points that achieved high prediction accuracy in distinguishing liver cancer patients from healthy individuals in SELDI-QqTOF profiles of serum.

Availability: MATLAB scripts to implement the methods described in this paper are available from the HWR's lab website http://lombardi.georgetown.edu/labpage

Contact:hwr@georgetown.edu

Keywords

Biomarker, mass spectrometry, peptides, proteins, spectrum, serum

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