Data

​Name Description​ Publication​
AberOWL Ontology repository and reasoning-as-a-service  Hoehndorf, R., Slater, L., Schofield, P. N., & Gkoutos, G. V. (2015). Aber-OWL: a framework for ontology-based data access in biology. BMC Bioinformatics, 16(1). https://doi.org/10.1186/s12859-015-0456-9
PhenomeNET Cross-species phenotype ontology and similarity computation  Hoehndorf, R., Schofield, P. N., & Gkoutos, G. V. (2011). PhenomeNET: a whole-phenome approach to disease gene discovery. Nucleic Acids Research, 39(18), e119–e119. https://doi.org/10.1093/nar/gkr538
PathoPhenoDB Database of pathogen-to-phenotype associations  Kafkas, Ş., Abdelhakim, M., Hashish, Y., Kulmanov, M., Abdellatif, M., Schofield, P. N., & Hoehndorf, R. (2019). PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research. Scientific Data, 6(1). https://doi.org/10.1038/s41597-019-0090-x
ICDPheno Phenotypes associated with diseases in the ICD  Kafkas, Ş., Althubaiti, S., Gkoutos, G. V., Hoehndorf, R., & Schofield, P. N. (2021). Linking common human diseases to their phenotypes; development of a resource for human phenomics. Journal of Biomedical Semantics, 12(1). https://doi.org/10.1186/s13326-021-00249-x
DDIEM Drug Database for Inborn Error of Metabolism  Abdelhakim, M., McMurray, E., Syed, A. R., Kafkas, S., Kamau, A. A., Schofield, P. N., & Hoehndorf, R. (2020). DDIEM: drug database for inborn errors of metabolism. Orphanet Journal of Rare Diseases, 15(1). https://doi.org/10.1186/s13023-020-01428-2
Phenotype Reactor  Database and website of phenotype associations   
EDAM-annotated ontologies​ ​A manually curated list of all ontologies in AberOWL annotated by topic, species and NCBI taxonomy Rodríguez-García MÁ, Slater L, Boudellioua I, Schofield P, Gkoutos G, Hoehndorf R (2016)Updates to the AberOWL ontology repository (ICBO BioCreative 2016)
 
PhenomeNet Similarity Matrix (Human)​ ​A matrix of PhenomeNet similarity scores between genes and OMIM IDs using human phenotypes only Boudellioua I, Razali RBM, Kulmanov M, Hashush Y, Bajic V,  Goncalves-Serra E, Schoenmakers N, Gkoutos GV, Schofield PN, Hoehndorf R (2017) Semantic prioritization of novel causative genomic variants. PLOS Computational Biology, https://doi.org/10.1371/journal.pcbi.1005500

Hoehndorf R, Schofield PN, Gkoutos GV (2011) PhenomeNET: a whole-phenome approach to disease gene discovery. Nuclein Acids Research, https://doi.org/10.1093/nar/gkr538
PhenomeNet Similarity Matrix (Mouse)​ ​A matrix of PhenomeNet similarity scores between genes and OMIM IDs using mouse phenotypes only Boudellioua I, Razali RBM, Kulmanov M, Hashush Y, Bajic V,  Goncalves-Serra E, Schoenmakers N, Gkoutos GV, Schofield PN, Hoehndorf R (2017) Semantic prioritization of novel causative genomic variants. PLOS Computational Biology, https://doi.org/10.1371/journal.pcbi.1005500

Hoehndorf R, Schofield PN, Gkoutos GV (2011) PhenomeNET: a whole-phenome approach to disease gene discovery. Nuclein Acids Research, https://doi.org/10.1093/nar/gkr538
Raw Exomes​ ​A set of synthetic exomes (VCF File Format) generated using ClinVar variants Boudellioua I, Razali RBM, Kulmanov M, Hashush Y, Bajic V,  Goncalves-Serra E, Schoenmakers N, Gkoutos GV, Schofield PN, Hoehndorf R (2017) Semantic prioritization of novel causative genomic variants. PLOS Computational Biology, https://doi.org/10.1371/journal.pcbi.1005500
Raw Exomes (MAF) ​A set of synthetic exomes (VCF File Format) generated using ClinVar variants, filtered by MAF < 1% Boudellioua I, Razali RBM, Kulmanov M, Hashush Y, Bajic V,  Goncalves-Serra E, Schoenmakers N, Gkoutos GV, Schofield PN, Hoehndorf R (2017) Semantic prioritization of novel causative genomic variants. PLOS Computational Biology, https://doi.org/10.1371/journal.pcbi.1005500
Raw Genomes​ ​A set of synthetic genomes (VCF File Format) generated using ClinVar variants Boudellioua I, Razali RBM, Kulmanov M, Hashush Y, Bajic V,  Goncalves-Serra E, Schoenmakers N, Gkoutos GV, Schofield PN, Hoehndorf R (2017) Semantic prioritization of novel causative genomic variants. PLOS Computational Biology, https://doi.org/10.1371/journal.pcbi.1005500
Raw Genomes (MAF) ​A set of synthetic genomes (VCF File Format) generated using ClinVar variants, filtered by MAF < 1% Boudellioua I, Razali RBM, Kulmanov M, Hashush Y, Bajic V,  Goncalves-Serra E, Schoenmakers N, Gkoutos GV, Schofield PN, Hoehndorf R (2017) Semantic prioritization of novel causative genomic variants. PLOS Computational Biology, https://doi.org/10.1371/journal.pcbi.1005500
RDF Knowledge Graph of proteins, drugs, diseases, functions and phenotypes ​An RDF dataset containing data on the following semantic types, gene, drug, protein function, disease Alshahrani M, Khan MA, Maddouri O, Kinjo AR, Queralt-Rosinach N, Hoehndorf R (2017) Neuro-symbolic representation learning on biological knowledge graphs. Bioinformatics btx275. doi:10.1093/bioinformatics/btx275
Knowledge Graph embeddings​ ​A knowledge graph embeddings containing of the RDF dataset mentioned above Alshahrani M, Khan MA, Maddouri O, Kinjo AR, Queralt-Rosinach N, Hoehndorf R (2017) Neuro-symbolic representation learning on biological knowledge graphs. Bioinformatics btx275. doi:10.1093/bioinformatics/btx275
Protein-protein interaction network embeddings for uniprot proteins​ ​Network embeddings generated with knowledge graph representation learning method Kulmanov M, Khan MA, Hoehndorf R (2017) DeepGO: Predicting protein functions from sequence and interactions using a deep ontology-aware classifier.  Bioinformatics, btx624, https://doi.org/10.1093/bioinformatics/btx624
Functions of CAFA3 targets ​Protein function predictions for CAFA3 targets by using DeepGO Kulmanov M, Khan MA, Hoehndorf R (2017) DeepGO: Predicting protein functions from sequence and interactions using a deep ontology-aware classifier.  Bioinformatics, btx624, https://doi.org/10.1093/bioinformatics/btx624
SIDER2DO ​Mapping between indications in SIDER and Disease Ontology ​Hoehndorf R, Schofield PN, Gkoutos GV (2015) Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases. Scientific Reports, doi: 10.1038/srep10888
Disease Similarity Matrix ​A disease-disease similarity matrix based on phenotype similarity, using Human Disease Ontology to represent diseases Hoehndorf R, Schofield PN, Gkoutos GV (2015) Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases. Scientific Reports, doi: 10.1038/srep10888
Disease-Disease drug similarity ​A file containing pairs of diseases (using Human Disease Ontology) treated with the same drugs Hoehndorf R, Schofield PN, Gkoutos GV (2015) Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases. Scientific Reports, doi: 10.1038/srep10888