| 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 |