- Poster presentation
- Open Access
Using a literature-based NMF model for discovering gene functional relationships
© Tjioe et al; licensee BioMed Central Ltd. 2008
Published: 8 July 2008
For a preliminary assessment of FAUN feature classification, each gene in the 50TG collection was classified based on its most dominant annotated feature or based on some feature weight threshold. The FAUN classification using the strongest feature (per gene) yielded 90% accuracy. A FAUN-based analysis of a new cerebellum gene set has revealed new knowledge – the gene set contains a large component of transcription factors.
This work is supported by an NIH-subcontract (HD052472) involving the University of Tennessee, University of Memphis, Oak Ridge National Laboratory, and the University of British Columbia.
- Berry MW, Browne M, Langville AN, Pauca VP, Plemmons RJ: Algorithms and Applications for Approximate Nonnegative Matrix Factorization. Computational Statistics & Data Analysis 2007, 52(1):155–173. 10.1016/j.csda.2006.11.006View ArticleGoogle Scholar
- Homayouni R, Heinrich K, Wei L, Berry MW: Gene clustering by latent semantic indexing of MEDLINE abstracts. Bioinformatics 2005, 21(1):104–115. 10.1093/bioinformatics/bth464View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd.