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BMCBI
2008

Extracting unrecognized gene relationships from the biomedical literature via matrix factorizations

13 years 11 months ago
Extracting unrecognized gene relationships from the biomedical literature via matrix factorizations
Background: The construction of literature-based networks of gene-gene interactions is one of the most important applications of text mining in bioinformatics. Extracting potential gene relationships from the biomedical literature may be helpful in building biological hypotheses that can be explored further experimentally. Recently, latent semantic indexing based on the singular value decomposition (LSI/SVD) has been applied to gene retrieval. However, the determination of the number of factors k used in the reduced rank matrix is still an open problem. Results: In this paper, we introduce a way to incorporate a priori knowledge of gene relationships into LSI/SVD to determine the number of factors. We also explore the utility of the non-negative matrix factorization (NMF) to extract unrecognized gene relationships from the biomedical literature by taking advantage of known gene relationships. A gene retrieval method based on NMF (GR/NMF) showed comparable performance with LSI/SVD. Con...
Hyunsoo Kim, Haesun Park, Barry L. Drake
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where BMCBI
Authors Hyunsoo Kim, Haesun Park, Barry L. Drake
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