About Abeer Almutari Abeer Almutari M.S. Student (former), Computer Science bioinformatics machine learning Abeer Almutari obtained her Master's degree in Computer Science under the supervision of Professor Robert Hoehndorf at Bio-Ontology Research Group at King Abdullah University of Science and Technology (KAUST). Research Interests Abeer's research interests included bioinformatics, machine learning and building new automated models using artificial intelligence. Education B.Sc. Electrical & Computer Engineering, King Abdul-Aziz University, Jeddah, Saudi Arabia, 2016 Projects Related Projects 2019 CompleX: Variant Prioritization in Complex Disease Tue, Jan 1 2019 - Fri, Dec 31 2021 Applied Ontology Neuro-Symbolic AI Rare disease Semantic similarity The hardest cases in clinical genome sequencing are the ones where no single variant explains the disease. As Mendelian gene discovery slows and the diagnostic rate for whole-exome sequencing stalls below 50%, growing evidence points to oligogenic and polygenic origins: combinations of medium-rare or common alleles that, individually, look unremarkable. Population-level approaches lack the power to find them, and traditional single-gene Mendelian reasoning ignores them. The CompleX project (2019–2021, with the Universities of Cambridge and Birmingham) set out to break this impasse by extending
CompleX: Variant Prioritization in Complex Disease Tue, Jan 1 2019 - Fri, Dec 31 2021 Applied Ontology Neuro-Symbolic AI Rare disease Semantic similarity The hardest cases in clinical genome sequencing are the ones where no single variant explains the disease. As Mendelian gene discovery slows and the diagnostic rate for whole-exome sequencing stalls below 50%, growing evidence points to oligogenic and polygenic origins: combinations of medium-rare or common alleles that, individually, look unremarkable. Population-level approaches lack the power to find them, and traditional single-gene Mendelian reasoning ignores them. The CompleX project (2019–2021, with the Universities of Cambridge and Birmingham) set out to break this impasse by extending
Related Sites Bio-Ontology Research Group (BORG) Computer Science (CS) Related Content Articles 1 Projects 1
