OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization | Zendy

Agne Antanaviciute | Zendy; Christopher M. Watson | Zendy; Sally M. Harrison | Zendy; Carolina Lascelles | Zendy; Laura A. Crinnion | Zendy; Alexander F. Markham | Zendy; David T. Bonthron | Zendy; Ian Carr | Zendy

Open Access

OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization

Author(s) -

Agne Antanaviciute,

Christopher M. Watson,

Sally M. Harrison,

Carolina Lascelles,

Laura A. Crinnion,

Alexander F. Markham,

David T. Bonthron,

Ian Carr

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv473

Subject(s) - uniprot , computer science , context (archaeology) , omim : online mendelian inheritance in man , computational biology , prioritization , candidate gene , exome , phenotype , bioinformatics , biology , exome sequencing , gene , genetics , paleontology , management science , economics

Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task.

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