Dumontier Lab

for Biomedical Knowledge Discovery

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Biochemical Semantic Web


Web search engines like Google are useful in helping you find web pages that you may have an interest in, but they have little capability in answering a question you might have. The reason for this is that information on the web is not represented in a machine understandable format, and as such, cannot be complexly queried nor precisely answered. If information were better structured, then we could use computers to reason about the information and infer knowledge that is explicit in our shared conceptualization, i.e. an ontology. Thus, by combining ontologies with existing information, we will be able to discover new knowledge, in that we will discover links between things that were not explicitly stated, but would be inferred on careful analysis. The primary goal of the Semantic Web is to add semantics to the current Web, in part, by designing ontologies which describe and relate concepts and objects using formal, logic-based representations.


A precise definition of ontologies can be found here. The W3C approved Web Ontology Language or OWL is a knowledge representation language for building Semantic Web ontologies. One variant of OWL, OWL-DL, is based on description logics (DL), a subset of First Order Logic that allows description of complex concepts from simpler ones with an emphasis on decidability of reasoning tasks. In other words, a feature of DLs is that reasoning tasks terminate after a finite amount of time and that the inferences drawn are valid. Reasoning tasks like checking ontology consistency, computing inferences, and realization (classification) can be executed by a computer program called a reasoner over DL ontologies. This is useful because the reasoner can identify inconsistencies and uncover non-obvious relations from our collective knowledge.


Our research aims to capture the semantics of biochemical knowledge such that computer-based inferences about structure and function become possible. The approach involves the design of biochemical ontologies and use of a reasoning-capable knowledge base. This research aims to form a cornerstone of the newly emerging semantic web so as to provide biochemical knowledge in a format that is amenable to computer-based reasoning. In combination with other complimentary efforts, we expect that new semantic links may be formed with our efforts, leading to improved data integration and powerful new data mining opportunities over heterogeneous biochemical knowledge.

Recent Work

See our OWL ontologies for knowledge representation and reasoning on the semantic web.
Describing chemical functional groups in OWL-DL for the classification of chemical compounds.
    PDF PDF sample data
Towards a Semantic Knowledge Base for Yeast Biologists.
    PDF OWL sample data
Integrated OWL and SWRL reasoning plugin for Protege-OWL 3.2.
   PDF software

Additional Resources

Relevant Publications