Cargando…
Gene function prediction in five model eukaryotes exclusively based on gene relative location through machine learning
The function of most genes is unknown. The best results in automated function prediction are obtained with machine learning-based methods that combine multiple data sources, typically sequence derived features, protein structure and interaction data. Even though there is ample evidence showing that...
Autores principales: | Pazos Obregón, Flavio, Silvera, Diego, Soto, Pablo, Yankilevich, Patricio, Guerberoff, Gustavo, Cantera, Rafael |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270439/ https://www.ncbi.nlm.nih.gov/pubmed/35803984 http://dx.doi.org/10.1038/s41598-022-15329-w |
Ejemplares similares
-
An improved catalogue of putative synaptic genes defined exclusively by temporal transcription profiles through an ensemble machine learning approach
por: Pazos Obregón, Flavio, et al.
Publicado: (2019) -
Putative synaptic genes defined from a Drosophila whole body developmental transcriptome by a machine learning approach
por: Pazos Obregón, Flavio, et al.
Publicado: (2015) -
IDconverter and IDClight: Conversion and annotation of gene and protein IDs
por: Alibés, Andreu, et al.
Publicado: (2007) -
Identifying essential genes across eukaryotes by machine learning
por: Beder, Thomas, et al.
Publicado: (2021) -
Genomic distribution of AFLP markers relative to gene locations for different eukaryotic species
por: Caballero, Armando, et al.
Publicado: (2013)