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Probabilistic framework for gene expression clustering validation based on gene ontology and graph theory

conference contribution
posted on 2008-01-01, 00:00 authored by Y Yuan, Chang-Tsun LiChang-Tsun Li
Based on the correlation between expression and ontology-driven gene similarity, we incorporate functional annotations into gene expression clustering validation. A probabilistic framework is proposed to accommodate incomplete annotations, after establishing a new term-term distance measure based on graph theory. Comprehensive evaluations are performed on six clustering algorithms. This study is the first to explore a robust quantitative functional relationship between clusters of genes. Such indices assess clustering quality in terms of consistency of annotation information and serve as new tools for combining biological knowledge with experimental data.

History

Event

IEEE Signal Processing Society. International Conference (2008 : Las Vegas, Nevada)

Series

IEEE Signal Processing Society International Conference

Pagination

625 - 628

Publisher

Institute of Electrical and Electronics Engineers

Location

Las Vegas, Nevada

Place of publication

Piscataway, N.J.

Start date

2008-03-30

End date

2008-04-04

ISSN

1520-6149

ISBN-13

9781424414840

ISBN-10

1424414849

Language

eng

Publication classification

E1.1 Full written paper - refereed

Editor/Contributor(s)

[Unknown]

Title of proceedings

ICASSP 2008 : Proceedings of the 2008 IEEE International Conference on Acoustics, Speech and Signal Processing