10.5281/zenodo.12493
https://zenodo.org/records/12493
oai:zenodo.org:12493
Collier, NIgel
NIgel
Collier
European Bioinformatics Institute
PhenoMiner database
Zenodo
2014
phenotype, natural language processing, OMIM, literature, ontology
2014-10-15
https://zenodo.org/communities/eu
Creative Commons Attribution 4.0 International
Phenotypes play a key role in inferring the complex relationships between genes and human heritable diseases. PhenoMiner is a research project aimed at the capture and encoding of phenotypes in the scientific literature. This should provide insights into the complex processes involved in human diseases as well as enabling semantic interoperability with existing biomedical ontologies such as those that describe human anatomy, genetics and behaviours.
The PhenoMiner database contains the results of an FP7 Marie Curie fellowship project on text/data-mining technology - natural language processing, machine learning and conceptual analysis. It builds on insights gained from semantic parsing to extract structured information about phenotypes from whole sentences - in contrast to existing techniques which often apply string matching. The system exploits the wealth of scientific data locked within the scientific literature in databases such as PubMed Central and Europe PMC to extract the semantic vocabulary of phenotypes that scientists use. The system will provide scientists, clinicians and informaticians with the data and tools they need to gain new insights into Mendelian diseases.
The database currently contains over 4800 phenotype terms automatically mined from full scientific articles and then associated to Online Mendelian Inheritance of Man (OMIM) disorders. All data is provided without manual filtering.
Please contact the author for further information and comments/suggestions.
- Nigel Collier (collier@ebi.ac.uk)
European Commission
10.13039/501100000780
301806
Semantic mining of phenotype associations from the biomedical literature