Extracting Unrecognized Gene Relationships From the Biomedical Literature via Matrix Factorizations Using a Priori Knowledge of Gene Relationships
Author(s)
Kim, Hyunsoo
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Abstract
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. In this paper, we
explore the utility of singular value decomposition (SVD) and nonnegative
matrix factorization (NMF) to extract unrecognized gene
relationships from the biomedical literature by taking advantage of
known gene relationships. We introduce a way to incorporate a
priori knowledge of gene relationships into LSI/SVD and NMF.
In addition, we propose a gene retrieval method based on NMF
(GR/NMF), which shows comparable performance with latent semantic
indexing based on SVD.
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Date
2006
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Text
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Technical Report