Applied Ontology

Data integration and ontologies for microbial cell factories

Ontology-based data integration for synthetic biology and metabolic engineering. Hoehndorf led the data-integration work package. Period: 2016–2018 Funding KAUST Center Competitive Funding — Grant ID: FCC/1/1976-08-01 (WP-lead) — USD 115,691 Team Vladimir Bajic — PI (Former KAUST CBRC director (retired)) Robert Hoehndorf — CoI (KAUST (Professor of Computer Science)) Miguel Angel Rodriguez Garcia — Postdoc (King Juan Carlos University (Research Scientist)) Software AberOWL — Ontology repository providing OWL EL reasoning services and SPARQL query expansion; integrates with PubMed/PMC for

Bio2Vec: Smart analytics infrastructure for the life sciences

Smart analytics infrastructure on biological knowledge graphs; extends Bio2RDF, develops semantic analytics methods that became OPA2Vec / OWL2Vec. Period: 2018–2020 Funding KAUST Competitive Research Grant — Grant ID: URF/1/3454-01-01 (PI) — USD 113,250 Team Robert Hoehndorf — PI (KAUST (Professor of Computer Science)) Xin Gao — CoI (KAUST (CBRC)) Michel Dumontier — CoI (Maastricht University) Jens Lehmann — CoI (Amazon (formerly TU Dresden)) Mona Alshahrani — PhD (alumnus) (Jubail University College (Assistant Professor)) Maxat Kulmanov — PhD (alumnus) (KAUST (Research Scientist)) Sumyyah

Improvement of genetic variant prioritization technology

Engineering improvements to the semantic variant-prioritization pipeline (PhenomeNet, DeepPVP). Period: 2018–2019 Funding KAUST Center Partnership Fund — Grant ID: FCS/1/3657-01-01 (PI) — USD 9,500 Team Robert Hoehndorf — PI (KAUST (Professor of Computer Science)) Paul N Schofield — CoI (University of Cambridge) Georgios V Gkoutos — CoI (University of Birmingham) Vladimir Bajic — CoI (Former KAUST CBRC director (retired)) Publications acknowledging this project (4) (2020) Semantic similarity and machine learning with biomedical ontologies (2019) Formal axioms in biomedical ontologies improve

CompleX: Variant Prioritization in Complex Disease

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

IBNSINA-QI: Integrating Biomedical Networks and Semantic Information for Neural network Analysis of Quantitative Information

Neuro-symbolic methods integrating biomedical networks and ontologies for quantitative analysis of disease phenotypes and variants. Period: 2021–2023 Funding KAUST Competitive Research Grant — Grant ID: URF/1/4355-01-01 (PI) — USD 239,999 Team Robert Hoehndorf — PI (KAUST (Professor of Computer Science)) Paul N Schofield — CoI (University of Cambridge) Georgios V Gkoutos — CoI (University of Birmingham) Sarah Alghamdi — PhD (alumnus) Azza Althagafi — PhD (alumnus) Sumyyah Toonsi — PhD (alumnus) Fernando Zhapa-Camacho — PhD (alumnus), MSc (alumnus) (KAUST) Xi Peng — MSc (alumnus) Zhenwei Tang —

Computational methods for functional metagenomics: from protein functions to multi-scale interactions

Multi-scale systems methods for characterising microbial community functions via protein function prediction; downstream produced DeepGOPlus and successor models. Period: 2022–2024 Funding KAUST Competitive Research Grant — Grant ID: URF/1/4675-01-01 (PI) — USD 247,500 Team Robert Hoehndorf — PI (KAUST (Professor of Computer Science)) Takashi Gojobori — CoI (KAUST (CBRC)) Maxat Kulmanov — PhD (alumnus), Postdoc (KAUST (Research Scientist)) Rund Tawfiq — PhD (alumnus) (Sano Centre Krakow (Postdoctoral researcher)) Daulet Toibazar — MSc (alumnus) Amal Alhelal — MSc (alumnus) Md Nurul Muttakin —
crg explainable ml ontologies

Towards sound, complete, and explainable machine learning with biomedical ontologies (CRG11)

Faithful, complete, and explainable machine-learning methods on biomedical ontologies. Grant URF/1/5041-01-01 activated Apr 2023. Period: 2023–2026 Funding KAUST Competitive Research Grant (CRG11) — Grant ID: URF/1/5041-01-01 (PI) Team Robert Hoehndorf — PI (KAUST (Professor of Computer Science)) Fernando Zhapa-Camacho — PhD (alumnus), Postdoc (KAUST) Mahdi Bu Ali — MSc (alumnus) Tengwei Song — Postdoc (KAUST) Software AbermOWL — Cloud-based federated reasoning system combining AberOWL with mOWL for symbolic + approximate neuro-symbolic reasoning over SROIQ(D). https://github.com/bio-ontology