JSM 2005 - Toronto

Abstract #303687

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 136
Type: Contributed
Date/Time: Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #303687
Title: Global Bayesian Approach to Identifying Biomarkers from MALDI-MS Data
Author(s): Junfeng Liu*+
Companies: Yale University
Address: 60 College Street, New Haven, CT, 06520-8034, United States
Keywords: Sample classification, ; mass spectrometry ; peak detection ; peak alignment ; reversible jump ; symmetric transition kernel
Abstract:

Mass spectrometry has been broadly used in biological research for biomarker discovery and pharmaceutical R&D. Beyond preliminary peak detection by certain threshold method, we develop a novel global simulation-based approach for peak alignment (biomarker identification). This is an improvement upon the first reversible jump Markov chain Monte Carlo algorithm initiated by Green (1995) on the dimension-matching problem. Our analysis is conducted on one cancer dataset and one healthy dataset. Finally, we do simulation for robustness test, give more convenient and powerful sample classification methods, and make comparison among different models.

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