Cargando…
GLIDE: combining local methods and diffusion state embeddings to predict missing interactions in biological networks
MOTIVATION: One of the core problems in the analysis of biological networks is the link prediction problem. In particular, existing interactions networks are noisy and incomplete snapshots of the true network, with many true links missing because those interactions have not yet been experimentally o...
Autores principales: | Devkota, Kapil, Murphy, James M, Cowen, Lenore J |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355260/ https://www.ncbi.nlm.nih.gov/pubmed/32657369 http://dx.doi.org/10.1093/bioinformatics/btaa459 |
Ejemplares similares
-
Higher-order genetic interaction discovery with network-based biological priors
por: Pellizzoni, Paolo, et al.
Publicado: (2023) -
GLIDER: function prediction from GLIDE-based neighborhoods
por: Devkota, Kapil, et al.
Publicado: (2022) -
Supervised biological network alignment with graph neural networks
por: Ding, Kerr, et al.
Publicado: (2023) -
A novel constrained genetic algorithm-based Boolean network inference method from steady-state gene expression data
por: Trinh, Hung-Cuong, et al.
Publicado: (2021) -
Characterizing alternative splicing effects on protein interaction networks with LINDA
por: Gjerga, Enio, et al.
Publicado: (2023)