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MATRIX FACTORIZATION-BASED DATA FUSION FOR GENE FUNCTION PREDICTION IN BAKER’S YEAST AND SLIME MOLD
The development of effective methods for the characterization of gene functions that are able to combine diverse data sources in a sound and easily-extendible way is an important goal in computational biology. We have previously developed a general matrix factorization-based data fusion approach for...
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| Main Authors: | , |
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| Format: | Artigo |
| Language: | Inglês |
| Published: |
2014
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3902649/ https://ncbi.nlm.nih.gov/pubmed/24297565 |
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