Cargando…
A Protein Interaction Information-based Generative Model for Enhancing Gene Clustering
In the field of computational bioinformatics, identifying a set of genes which are responsible for a particular cellular mechanism, is very much essential for tasks such as medical diagnosis or disease gene identification. Accurately grouping (clustering) the genes is one of the important tasks in u...
Autores principales: | Dutta, Pratik, Saha, Sriparna, Pai, Sanket, Kumar, Aviral |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6971242/ https://www.ncbi.nlm.nih.gov/pubmed/31959782 http://dx.doi.org/10.1038/s41598-020-57437-5 |
Ejemplares similares
-
Amalgamation of 3D structure and sequence information for protein–protein interaction prediction
por: Jha, Kanchan, et al.
Publicado: (2020) -
Graph-BERT and language model-based framework for protein–protein interaction identification
por: Jha, Kanchan, et al.
Publicado: (2023) -
Unsupervised gene selection using biological knowledge : application in sample clustering
por: Acharya, Sudipta, et al.
Publicado: (2017) -
Prediction of protein–protein interaction using graph neural networks
por: Jha, Kanchan, et al.
Publicado: (2022) -
A multiobjective multi-view cluster ensemble technique: Application in patient subclassification
por: Mitra, Sayantan, et al.
Publicado: (2019)