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SENT: semantic features in text
We present SENT (semantic features in text), a functional interpretation tool based on literature analysis. SENT uses Non-negative Matrix Factorization to identify topics in the scientific articles related to a collection of genes or their products, and use them to group and summarize these genes. I...
| Autores principales: | , , , , , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2009
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703940/ https://www.ncbi.nlm.nih.gov/pubmed/19458159 http://dx.doi.org/10.1093/nar/gkp392 |