Cargando…
Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein–Protein Interaction Network
High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interact...
Autores principales: | Cao, Buwen, Deng, Shuguang, Qin, Hua, Ding, Pingjian, Chen, Shaopeng, Li, Guanghui |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6100434/ https://www.ncbi.nlm.nih.gov/pubmed/29914123 http://dx.doi.org/10.3390/molecules23061460 |
Ejemplares similares
-
Low-Rank and Sparse Matrix Decomposition for Genetic
Interaction Data
por: Wang, Yishu, et al.
Publicado: (2015) -
Modular decomposition of protein-protein interaction networks
por: Gagneur, Julien, et al.
Publicado: (2004) -
Dissecting the Human Protein-Protein Interaction Network via Phylogenetic Decomposition
por: Chen, Cho-Yi, et al.
Publicado: (2014) -
Prediction of Protein–Protein Interactions with Clustered Amino Acids and Weighted Sparse Representation
por: Huang, Qiaoying, et al.
Publicado: (2015) -
Completing sparse and disconnected protein-protein network by deep learning
por: Huang, Lei, et al.
Publicado: (2018)