Cargando…
Prediction of Heterodimeric Protein Complexes from Weighted Protein-Protein Interaction Networks Using Novel Features and Kernel Functions
Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been deve...
Autores principales: | Ruan, Peiying, Hayashida, Morihiro, Maruyama, Osamu, Akutsu, Tatsuya |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3679142/ https://www.ncbi.nlm.nih.gov/pubmed/23776458 http://dx.doi.org/10.1371/journal.pone.0065265 |
Ejemplares similares
-
Improving prediction of heterodimeric protein complexes using combination with pairwise kernel
por: Ruan, Peiying, et al.
Publicado: (2018) -
Prediction of heterotrimeric protein complexes by two-phase learning using neighboring kernels
por: Ruan, Peiying, et al.
Publicado: (2014) -
Determining the minimum number of protein-protein interactions required to support known protein complexes
por: Nakajima, Natsu, et al.
Publicado: (2018) -
Prediction of Protein-Protein Interaction Strength Using Domain Features with Supervised Regression
por: Kamada, Mayumi, et al.
Publicado: (2014) -
Heterodimeric protein complex identification by naïve Bayes classifiers
por: Maruyama, Osamu
Publicado: (2013)