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Experiences Using Logic Programming in Bioinformatics

  • Chris Mungall
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5649)

Abstract

Reverse engineering complex biological systems requires the integration of multiple different databases using detailed background knowledge. Logic programming can provide a means of both performing integrative queries and rule-based inference to account for implicit knowledge.

The Biological Logic Programming toolkit (Blipkit) was developed as a means of doing this kind of data integration. Implemented in SWI-Prolog, Blipkit has models of different aspects of life sciences data, including genes and gene sequences, RNA structures, evolutionary relationships, phenotypes and biological interactions. These can be combined to answer complex questions spanning multiple datasources. Blipkit also has means of integrating with and combining life sciences databases and ontologies.

Keywords

Logic Program Logic Programming Biomedical Ontology Prolog System Sequence Ontology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© Springer-Verlag Berlin Heidelberg 2009

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  • Chris Mungall

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