Cargando…
Identifying disease genes using machine learning and gene functional similarities, assessed through Gene Ontology
Identifying disease genes from a vast amount of genetic data is one of the most challenging tasks in the post-genomic era. Also, complex diseases present highly heterogeneous genotype, which difficult biological marker identification. Machine learning methods are widely used to identify these marker...
Autores principales: | Asif, Muhammad, Martiniano, Hugo F. M. C. M., Vicente, Astrid M., Couto, Francisco M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6287949/ https://www.ncbi.nlm.nih.gov/pubmed/30532199 http://dx.doi.org/10.1371/journal.pone.0208626 |
Ejemplares similares
-
DGH-GO: dissecting the genetic heterogeneity of complex diseases using gene ontology
por: Asif, Muhammad, et al.
Publicado: (2023) -
CrowdGO: Machine learning and semantic similarity guided consensus Gene Ontology annotation
por: Reijnders, Maarten J. M. F., et al.
Publicado: (2022) -
Identification of biological mechanisms underlying a multidimensional ASD phenotype using machine learning
por: Asif, Muhammad, et al.
Publicado: (2020) -
Disjunctive shared information between ontology concepts: application to Gene Ontology
por: Couto, Francisco M, et al.
Publicado: (2011) -
Semantic similarity and machine learning with ontologies
por: Kulmanov, Maxat, et al.
Publicado: (2020)