Name
Abstract | ||
|---|---|---|
A large number of biomedical resources have been developed to represent the functions of biological entities, and these resources are widely used for data integration and analysis. Expressing functions in biomedical ontologies currently uses formal representation patterns that renders basic reasoning tasks to fall in complexity classes beyond polynomial time, thereby limiting the potential of using knowledge-based methods for data integration, querying or quality control. Here, we propose an alternative representation pattern for expressing knowledge about biological functions, together with a biological and ontological justification, which can be expressed using the description logic EL++ and implemented using the OWL 2 EL profile. To demonstrate the utility of our account of biological functions, we apply it to all proteins contained in the SwissProt database and evaluate its utility with respect to answering complex queries as well with respect to the classification and query times. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.3233/978-1-61499-660-6-299 | Frontiers in Artificial Intelligence and Applications |
Keywords | Field | DocType |
protein,biological function,tractable reasoning,Big Ontologies | Data science,Open Biomedical Ontologies,Computer science,Knowledge management | Conference |
Volume | ISSN | Citations |
283 | 0922-6389 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert Hoehndorf | 1 | 667 | 53.18 |
| Liam Mencel | 2 | 0 | 0.68 |
| Georgios V. Gkoutos | 3 | 399 | 36.73 |
| Paul N. Schofield | 4 | 319 | 25.71 |