Abstract
Increasingly sophisticated knowledge about RNA structure and function requires an inclusive knowledge representation that facilitates the integration of independently –generated information arising from such efforts as genome sequencing projects, microarray analyses, structure determination and RNA SELEX experiments. While RNAML, an XML-based representation, has been proposed as an exchange format for a select subset of information, it lacks domain-specific semantics that are essential for answering questions that require expert knowledge. Here, we describe an RNA knowledge base (RKB) for structure-based knowledge using RDF/OWL Semantic Web technologies. RKB extends a number of ontologies and contains basic terminology for nucleic acid composition along with context/model-specific structural features such as sugar conformations, base pairings and base stackings. RKB (available at http://semanticscience.org/projects/rkb) is populated with PDB entries and MC-Annotate structural annotation. We show queries to the RKB using description logic reasoning, thus opening the door to question answering over independently-published RNA knowledge using Semantic Web technologies.
Highlights
The ability to accurately capture biomolecular behaviour is critical to our understanding of cellular systems
We show queries to the Ribonucleic acids (RNAs) knowledge base (RKB) using description logic reasoning, opening the door to question answering over independently-published RNA knowledge using Semantic Web technologies
This project pursued four main objectives: i) to unequivocally represent basic biochemical knowledge about nucleic acids and their structural characteristics, ii) to accurately capture the knowledge generated by a nucleic acid structural feature annotator such as MC-Annotate in such a way that it complemented other structural or functional knowledge, iii) to implement a scheme for the representation of knowledge obtained as information from a computational procedure, iv) to maximize interoperability with a set of trusted external ontologies
Summary
The ability to accurately capture biomolecular behaviour is critical to our understanding of cellular systems. The set of entities, objects and relations used by scientists, through their lingua franca, defines a conceptualization of their subjects of study. The explicit commitment to a conceptualization enables scientists to share knowledge, and permits the creation of machine-understandable knowledge bases. An ontology is an explicit specification of a conceptualization of a particular domain of knowledge [1], in which the set of objects and their relations define its scope. Biological situational modelling [2,3] has been used as a methodology to capture this knowledge in a precise and accurate manner, so that conflicting statements about biochemical entities may be tolerated provided there exists some circumstantial qualification. A long term solution for knowledge representation in the life sciences must consider context, in addition to identity and action
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