Large-Scale Reasoning over Functions in Biomedical Ontologies

被引:3
|
作者
Hoehndorf, Robert [1 ]
Mencel, Liam [1 ]
Gkoutos, Georgios V. [2 ,3 ]
Schofield, Paul N. [4 ]
机构
[1] King Abdullah Univ Sci & Technol, Comp Elect & Math Sci & Engn Div, Computat Biosci Res Ctr, 4700 KAUST, Thuwal 239556900, Saudi Arabia
[2] Univ Birmingham, Ctr Computat Biol, Inst Canc & Genom Sci, Coll Med & Dent Sci, Birmingham B15 2TT, W Midlands, England
[3] Univ Hosp Birmingham NHS Fdn Trust, Inst Translat Med, Birmingham B15 2TT, W Midlands, England
[4] Univ Cambridge, Dept Physiol Dev & Neurosci, Downing St, Cambridge CB2 3EG, England
来源
关键词
protein; biological function; tractable reasoning; Big Ontologies; GENE ONTOLOGY; DATABASE; OBO; OWL;
D O I
10.3233/978-1-61499-660-6-299
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:299 / 312
页数:14
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