Semantic prioritization of novel causative genomic variants.
Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of fea...
Main Authors: | Imane Boudellioua, Rozaimi B Mahamad Razali, Maxat Kulmanov, Yasmeen Hashish, Vladimir B Bajic, Eva Goncalves-Serra, Nadia Schoenmakers, Georgios V Gkoutos, Paul N Schofield, Robert Hoehndorf |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2017-04-01
|
Series: | PLoS Computational Biology |
Online Access: | https://doi.org/10.1371/journal.pcbi.1005500 |
Similar Items
-
DeepPVP: phenotype-based prioritization of causative variants using deep learning
by: Imane Boudellioua, et al.
Published: (2019-02-01) -
Semantic Prioritization of Novel Causative Genomic Variants in Mendelian and Oligogenic Diseases
by: Boudellioua, Imene
Published: (2019) -
DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier.
by: Maxat Kulmanov, et al.
Published: (2020-11-01) -
Improving disease gene prioritization by comparing the semantic similarity of phenotypes in mice with those of human diseases.
by: Anika Oellrich, et al.
Published: (2012-01-01) -
Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies
by: Luke T. Slater, et al.
Published: (2020-12-01)