Representation of probabilistic scientific knowledge

The theory of probability is widely used in biomedical research for data analysis and modelling. In previous work the probabilities of the research hypotheses have been recorded as experimental metadata. The ontology HELO is designed to support probabilistic reasoning, and provides semantic descript...

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Bibliographic Details
Published in:Journal of biomedical semantics 2013-04, Vol.4 Suppl 1 (Suppl 1), p.S7-S7
Main Authors: Soldatova, Larisa N, Rzhetsky, Andrey, De Grave, Kurt, King, Ross D
Format: Article
Language:English
Subjects:
Amino acids
Biomedical data
Data analysis
Drug development
Hypotheses
Knowledge
Knowledge representation
Laboratories
Learning
Life span
Mathematical functions
Medical research
Ontology
Probabilistic inference
Probability
Proceedings
Semantics
Sirtuins
Statistical analysis
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Summary:The theory of probability is widely used in biomedical research for data analysis and modelling. In previous work the probabilities of the research hypotheses have been recorded as experimental metadata. The ontology HELO is designed to support probabilistic reasoning, and provides semantic descriptors for reporting on research that involves operations with probabilities. HELO explicitly links research statements such as hypotheses, models, laws, conclusions, etc. to the associated probabilities of these statements being true. HELO enables the explicit semantic representation and accurate recording of probabilities in hypotheses, as well as the inference methods used to generate and update those hypotheses. We demonstrate the utility of HELO on three worked examples: changes in the probability of the hypothesis that sirtuins regulate human life span; changes in the probability of hypotheses about gene functions in the S. cerevisiae aromatic amino acid pathway; and the use of active learning in drug design (quantitative structure activity relation learning), where a strategy for the selection of compounds with the highest probability of improving on the best known compound was used. HELO is open source and available at https://github.com/larisa-soldatova/HELO.
ISSN:2041-1480
2041-1480
DOI:10.1186/2041-1480-4-S1-S7