Cargando…
Integrating Semantic Information into Multiple Kernels for Protein-Protein Interaction Extraction from Biomedical Literatures
Protein-Protein Interaction (PPI) extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were...
Autores principales: | Li, Lishuang, Zhang, Panpan, Zheng, Tianfu, Zhang, Hongying, Jiang, Zhenchao, Huang, Degen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3951470/ https://www.ncbi.nlm.nih.gov/pubmed/24622773 http://dx.doi.org/10.1371/journal.pone.0091898 |
Ejemplares similares
-
Leveraging syntactic and semantic graph kernels to extract pharmacokinetic drug drug interactions from biomedical literature
por: Zhang, Yaoyun, et al.
Publicado: (2016) -
Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature
por: Murugesan, Gurusamy, et al.
Publicado: (2017) -
Protein interaction sentence detection using multiple semantic kernels
por: Polajnar, Tamara, et al.
Publicado: (2011) -
Extracting semantically enriched events from biomedical literature
por: Miwa, Makoto, et al.
Publicado: (2012) -
Exploiting syntactic and semantics information for chemical–disease relation extraction
por: Zhou, Huiwei, et al.
Publicado: (2016)