Cargando…
Efficient Prediction of Progesterone Receptor Interactome Using a Support Vector Machine Model
Protein-protein interaction (PPI) is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researchers. So far, most computational studies of PPI are intended for pair-wise prediction. Theoretically, predicting protein partners for a single protein is...
Autores principales: | Liu, Ji-Long, Peng, Ying, Fu, Yong-Sheng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4394448/ https://www.ncbi.nlm.nih.gov/pubmed/25741764 http://dx.doi.org/10.3390/ijms16034774 |
Ejemplares similares
-
Mammalian MicroRNA Prediction through a Support Vector Machine Model of Sequence and Structure
por: Sheng, Ying, et al.
Publicado: (2007) -
Machine learning prediction model based on enhanced bat algorithm and support vector machine for slow employment prediction
por: Wei, Yan, et al.
Publicado: (2023) -
Learning with Support Vector Machines
por: Campbell, Colin, et al.
Publicado: (2010) -
Tyrosine Kinase Ligand-Receptor Pair Prediction by Using Support Vector Machine
por: Yarimizu, Masayuki, et al.
Publicado: (2015) -
Support Vector Machine Model Predicts Dose for Organs at Risk in High-Dose Rate Brachytherapy of Cervical Cancer
por: Zhou, Ping, et al.
Publicado: (2021)