Geometric Hashing: An Overview
IEEE Computational Science & Engineering
Applying Constraint Programming to Protein Structure Determination
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Logic Programming Techniques in Protein Structure Determination: Methodologies and Results
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Clp-based protein fragment assembly*
Theory and Practice of Logic Programming
A filtering technique for fragment assembly- based proteins loop modeling with constraints
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
A constraint solver for flexible protein models
Journal of Artificial Intelligence Research
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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.