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...

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Detalles Bibliográficos
Autores principales: Vazquez, Miguel, Carmona-Saez, Pedro, Nogales-Cadenas, Ruben, Chagoyen, Monica, Tirado, Francisco, Carazo, Jose Maria, Pascual-Montano, Alberto
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Articles
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

Internet

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

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