Metarel, an ontology facilitating advanced querying of biomedical knowledge

Knowledge management has become indispensible in the Life Sciences for integrating and querying the enormous amounts of detailed knowledge about genes, organisms, diseases, drugs, cells, etc. Such detailed knowledge is continuously generated in bioinformatics via both hardware (e.g. raw data dumps from micro‐arrays) and software (e.g. computational analysis of data). Well‐known frameworks for managing knowledge are relational databases and spreadsheets. The doctoral dissertation describes knowledge management in two more recently‐investigated frameworks: ontologies and the Semantic Web. Knowledge statements like ‘lions live in Africa’ and ‘genes are located in a cell nucleus’ are managed with the use of URIs, logics and the ontological distinction between instances and classes. Both theory and practice are described. Metarel, the core subject of the dissertation, is an ontology describing relations that can bridge the mismatch between network‐based relations that appeal to internet browsing and logic‐based relations that are formally expressed in Description Logic. Another important subject of the dissertation is BioGateway, which is a knowledge base that has integrated biomedical knowledge in the form of hundreds of millions of network‐based relations in the RDF format. Metarel was used to upgrade the logical meaning of these relations towards Description Logic. This has enabled to build a computer reasoner that could run over the knowledge base and derive new knowledge statements

Flexibility and utility of the cell cycle ontology

The Cell Cycle Ontology (CCO) has the aim to provide a 'one stop shop' for scientists interested in the biology of the cell cycle that would like to ask questions from a molecular and/or systems perspective: what are the genes, proteins, and so on involved in the regulation of cell division? How do they interact to produce the effects observed in the regulation of the cell cycle? To answer these questions, the CCO must integrate a large amount of knowledge from diverse sources; the irregularity and incompleteness of this information suggests an ontology can act as the means of this integration. The volatility and continued expansion of biological knowledge means the content and modelling of the CCO will have to be frequently changed and updated. The CCO is generated from the input data automatically once every two months. This makes it easy to change the representation to enable certain queries; incorporate new knowledge; and consistently apply design patterns across the CCO. The automatic process also allows the CCO to be delivered in a variety of representations that suit the needs of various CCO customers and the abilities of existing toolsets. In this paper we present the CCO and its characteristics of utility and flexibility, that, from our perspective, make it a beautiful ontology