CompleX: Variant Prioritization in Complex Disease
Overview
Semantic methods for prioritising causative variants in complex (polygenic / oligogenic) disease using phenotype ontologies and gene network embeddings.
Period: 2019–2021
Funding
- KAUST Competitive Research Grant
— Grant ID:
URF/1/3790-01-01(PI) — USD 240,000
Team
- Robert Hoehndorf — PI (KAUST (Professor of Computer Science))
- Paul N Schofield — CoI (University of Cambridge)
- Georgios V Gkoutos — CoI (University of Birmingham)
- Imane Boudellioua — PhD (alumnus) (King Fahd University of Petroleum and Minerals (Assistant Professor))
- Mona Alshahrani — PhD (alumnus) (Jubail University College (Assistant Professor))
- Sarah Alghamdi — PhD (alumnus)
- Azza Althagafi — PhD (alumnus), MSc (alumnus)
- Abeer Almutairi — MSc (alumnus)
- Sara Althubaiti — MSc (alumnus)
- Hatoon Al Ali — MSc (alumnus)
- Safana Bakheet — MSc (alumnus)
- Ashraf Kibraya — Postdoc
Software
- OPA2Vec — Ontology Property Alignment to Vector representations; integrates ontology axioms with metadata text for embeddings. https://github.com/bio-ontology-research-group/opa2vec
- PhenomeNet — Cross-species phenotype network combining HPO, MPO, ZP and others, with semantic-similarity-based gene-disease prediction. https://github.com/bio-ontology-research-group/phenomenet
Publications acknowledging this project (17)
- (2021) How much do model organism phenotypes contribute to the computational identification of human disease genes?
- (2020) DeepGOWeb: Fast and accurate protein function prediction on the (Semantic) Web
- (2020) Semantic similarity and machine learning with biomedical ontologies
- (2019) DeepGOPlus: Improved protein function prediction from sequence
- (2019) PathoPhenoDB: linking human pathogens to their disease phenotypes in support of infectious disease research
- (2015) Ontology-based prediction of cancer driver genes
- (2015) Klarigi: Explanations for Semantic Groupings Supplementary Material
- (2012) DDIEM: Drug Database for Inborn Errors of Metabolism
- (2012) Linking common human diseases to their phenotypes; development of a resource for human phenomics
- (2012) Komenti: A Semantic Text-mining Framework
- (2012) Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies
- (2012) Improved characterisation of clinical text through ontology-based vocabulary expansion
- () PhenomeBrowser: Integrating phenotypes, their semantics, and phenotype-based machine learning across domains, organisms, and applications
- () Klarigi: Characteristic Explanations for Semantic Data
- () Klarigi: Characteristic Explanations for Semantic Data
- … and 2 more.
Topics: Applied Ontology, Neuro-symbolic AI, Rare disease, Semantic similarity