The diagnosis of rare diseases requires the integration of patient-specific data with large-scale background knowledge, such as the Human Phenotype Ontology (HPO). We develop systems like PhenomeNET and PVP that use automated reasoning and machine learning to prioritize disease-causing genomic variants based on their phenotypic consequences.
- Section
- Applications
- Keywords
- PhenomeNET, DeepPVP, PVP, variant prioritization, Human Phenotype Ontology, HPO, rare disease, complex disease, consanguinity, Saudi population
Connections
related papers borg:linkedPaper
- DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier
- DDIEM: drug database for inborn errors of metabolism
- What is the right sequencing approach? Solo VS extended family analysis in consanguineous populations
- Contribution of model organism phenotypes to the computational identification of human disease genes
- DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning
- Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learning
- CAGI6 ID panel challenge: assessment of phenotype and variant predictions in 415 children with neurodevelopmental disorders (NDDs)
- Predicting candidate genes from phenotypes, functions and anatomical site of expression
- Ontology based text mining of gene-phenotype associations: application to candidate gene prediction
- DeepPVP: phenotype-based prioritization of causative variants using deep learning
- Similarity-based search of model organism, disease and drug effect phenotypes
- Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases
- Starvar: symptom-based tool for automatic ranking of variants using evidence from literature and genomes
- The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients
- Genomic landscape of retinoblastoma: Insights into risk stratification and precision pediatric Neuro-Oncology
- OligoPVP: Phenotype-driven analysis of individual genomic information to prioritize oligogenic disease variants
- PathoPhenoDB: linking human pathogens to their disease phenotypes in support of infectious disease research
- Semantic prioritization of novel causative genomic variants
- Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes
- Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project
- Causal relationships between diseases mined from the literature improve the use of polygenic risk scores
- EMC10 homozygous variant identified in a family with global developmental delay, mild intellectual disability, and speech delay
- PhenomeNET: a whole-phenome approach to disease gene discovery
- PIDO: The Primary Immunodeficiency Disease Ontology
- New approaches to the representation and analysis of phenotype knowledge in human diseases and their animal models
- Linking PharmGKB to phenotype studies and animal models of disease for drug repurposing
- Mouse genetic and phenotypic resources for human genetics
- An integrative, translational approach to understanding rare and orphan genetically based diseases
- Mouse model phenotypes provide information about human drug targets
- Integrating phenotype ontologies with PhenomeNET
- Phenotype-driven discovery of digenic variants in personal genome sequences
- A translational medicine approach to orphan diseases
related projects borg:linkedProject
- Personalized cancer treatment prediction (KCSH Pathway to Impact 2025)
- KAUST Center of Excellence for Generative AI (Health and Wellness, BCB theme)
- Disease Models from Patient-derived Leukemic Cells in Biomimetic Peptide Scaffolds for Precision Medicine Applications
- A public Saudi pangenome as reference for genomics in the Middle East
- IBNSINA-QI: Integrating Biomedical Networks and Semantic Information for Neural network Analysis of Quantitative Information
- CompleX: Variant Prioritization in Complex Disease
- Improving health of Saudi population
- Whole genome sequencing of rare disease patients
- Improvement of genetic variant prioritization technology
related people borg:linkedPerson
- Robert Hoehndorf
- Mona Alshahrani
- Sarah Alghamdi
- Sumyyah Toonsi
- Sara Althubaiti
- Maxat Kulmanov
- Imane Boudellioua
- Azza Althagafi
- Miguel Angel Rodriguez Garcia
- Zhenwei Tang
- Yang Liu
- Xi Peng
- Paul N Schofield
- Charlotte Hauser
- Malak Althagafi
- Georgios V Gkoutos
- Vladimir Bajic
- Fernando Zhapa-Camacho
- Sakhaa Alsaedi
- Abeer Almutairi
- Hatoon Al Ali
- Safana Bakheet
- Sawsan Al Boeisa
- Mahdi Bu Ali
- Ashraf Kibraya
- Aleksei Matveev
Referenced by
research topics borg:topic
- Personalized cancer treatment prediction (KCSH Pathway to Impact 2025)
- KAUST Center of Excellence for Generative AI (Health and Wellness, BCB theme)
- Disease Models from Patient-derived Leukemic Cells in Biomimetic Peptide Scaffolds for Precision Medicine Applications
- A public Saudi pangenome as reference for genomics in the Middle East
- IBNSINA-QI: Integrating Biomedical Networks and Semantic Information for Neural network Analysis of Quantitative Information
- CompleX: Variant Prioritization in Complex Disease
- Improving health of Saudi population
- Whole genome sequencing of rare disease patients
- Improvement of genetic variant prioritization technology
- Robert Hoehndorf
- Imane Boudellioua
- Mona Alshahrani
- Maxat Kulmanov
- Sarah Alghamdi
- Azza Althagafi
- Sumyyah Toonsi
- Yang Liu
- Fernando Zhapa-Camacho
- Sakhaa Alsaedi
- Abeer Almutairi
- Sara Althubaiti
- Hatoon Al Ali
- Xi Peng
- Zhenwei Tang
- Safana Bakheet
- Sawsan Al Boeisa
- Mahdi Bu Ali
- Miguel Angel Rodriguez Garcia
- Ashraf Kibraya
- Aleksei Matveev
- Charlotte Hauser
- Malak Althagafi
- Paul N Schofield
- Georgios V Gkoutos
- Vladimir Bajic
- DDIEM: drug database for inborn errors of metabolism
- Phenotype-driven discovery of digenic variants in personal genome sequences
- The application of Large Language Models to the phenotype-based prioritization of causative genes in rare disease patients
- PathoPhenoDB: linking human pathogens to their disease phenotypes in support of infectious disease research
- Integrating phenotype ontologies with PhenomeNET
- Starvar: symptom-based tool for automatic ranking of variants using evidence from literature and genomes
- Ontology based text mining of gene-phenotype associations: application to candidate gene prediction
- DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier
- What is the right sequencing approach? Solo VS extended family analysis in consanguineous populations
- Contribution of model organism phenotypes to the computational identification of human disease genes
- DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning
- Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learning
- CAGI6 ID panel challenge: assessment of phenotype and variant predictions in 415 children with neurodevelopmental disorders (NDDs)
- Predicting candidate genes from phenotypes, functions and anatomical site of expression
- DeepPVP: phenotype-based prioritization of causative variants using deep learning
- Similarity-based search of model organism, disease and drug effect phenotypes
- Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases
- Genomic landscape of retinoblastoma: Insights into risk stratification and precision pediatric Neuro-Oncology
- OligoPVP: Phenotype-driven analysis of individual genomic information to prioritize oligogenic disease variants
- Semantic prioritization of novel causative genomic variants
- Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes
- Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project
- Causal relationships between diseases mined from the literature improve the use of polygenic risk scores
- EMC10 homozygous variant identified in a family with global developmental delay, mild intellectual disability, and speech delay
- PhenomeNET: a whole-phenome approach to disease gene discovery
- PIDO: The Primary Immunodeficiency Disease Ontology
- New approaches to the representation and analysis of phenotype knowledge in human diseases and their animal models
- Linking PharmGKB to phenotype studies and animal models of disease for drug repurposing
- Mouse genetic and phenotypic resources for human genetics
- An integrative, translational approach to understanding rare and orphan genetically based diseases
- Mouse model phenotypes provide information about human drug targets
- A translational medicine approach to orphan diseases
Open in the interactive graph →
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