Format

Send to

Choose Destination
J Comput Biol. 2009 Aug;16(8):1183-93. doi: 10.1089/cmb.2009.0018.

A bayesian approach to protein inference problem in shotgun proteomics.

Author information

1
School of Informatics, Indiana University , Bloomington, IN 47408, USA.

Abstract

The protein inference problem represents a major challenge in shotgun proteomics. In this article, we describe a novel Bayesian approach to address this challenge by incorporating the predicted peptide detectabilities as the prior probabilities of peptide identification. We propose a rigorious probabilistic model for protein inference and provide practical algoritmic solutions to this problem. We used a complex synthetic protein mixture to test our method and obtained promising results.

PMID:
19645593
PMCID:
PMC2799497
DOI:
10.1089/cmb.2009.0018
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for PubMed Central
Loading ...
Support Center