Cargando…
Conjoint Feature Representation of GO and Protein Sequence for PPI Prediction Based on an Inception RNN Attention Network
Protein-protein interactions (PPIs) are pivotal for cellular functions and biological processes. In the past years, computational methods using amino acid sequences and gene ontology (GO) annotations of proteins for prioritizing PPIs have provided important references for biological experiments in t...
Autores principales: | Zhao, Lingling, Wang, Junjie, Hu, Yang, Cheng, Liang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Gene & Cell Therapy
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515979/ https://www.ncbi.nlm.nih.gov/pubmed/33230427 http://dx.doi.org/10.1016/j.omtn.2020.08.025 |
Ejemplares similares
-
Representation Learning of Logic Words by an RNN: From Word Sequences to Robot Actions
por: Yamada, Tatsuro, et al.
Publicado: (2017) -
Learning Hierarchical Representations with Spike-and-Slab Inception Network
por: Qiao, Weizheng, et al.
Publicado: (2021) -
Automatic cardiac arrhythmias classification using CNN and attention‐based RNN network
por: Sun, Jie
Publicado: (2023) -
Learning Representations Using RNN Encoder-Decoder for Edge Security Control
por: Guo, Wei, et al.
Publicado: (2022) -
Hierarchical representation for PPI sites prediction
por: Quadrini, Michela, et al.
Publicado: (2022)