Constraint Programming in Structural Bioinformatics

Bioinformatics aims at applying computer science methods to the wealth of data collected in a variety of experiments in life sciences (e.g. cell and molecular biology, biochemistry, medicine, etc.) in order to help analysing such data and eliciting new knowledge from it. In addition to string proces...

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Bibliographic Details
Published in:Constraints : an international journal 2008-06, Vol.13 (1-2), p.3-20
Main Authors: Barahona, Pedro, Krippahl, Ludwig
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computer Science
Operations Research/Decision Theory
Optimization
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Summary:Bioinformatics aims at applying computer science methods to the wealth of data collected in a variety of experiments in life sciences (e.g. cell and molecular biology, biochemistry, medicine, etc.) in order to help analysing such data and eliciting new knowledge from it. In addition to string processing bioinformatics is often identified with machine learning used for mining the large banks of bio-data available in electronic format, namely in a number of web servers. Nevertheless, there are opportunities of applying other computational techniques in some bioinformatics applications. In this paper, we report the application of constraint programming to address two structural bioinformatics problems, protein structure prediction and protein interaction (docking). The efficient application of constraint programming requires innovative modelling of these problems, as well as the development of advanced propagation techniques (e.g. global reasoning and propagation), which were adopted in Chemera, a system that is currently used to support biochemists in their research.
ISSN:1383-7133
1572-9354
DOI:10.1007/s10601-007-9036-6