A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Fast protein folding in the hydrophobic-hydrophilic model within three-eights of optimal
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Chain growth algorithms for HP-type lattice proteins
RECOMB '97 Proceedings of the first annual international conference on Computational molecular biology
Protein folding in the hydrophobic-hydrophilic (HP) is NP-complete
RECOMB '98 Proceedings of the second annual international conference on Computational molecular biology
On the complexity of protein folding (abstract)
RECOMB '98 Proceedings of the second annual international conference on Computational molecular biology
A Sufficient Condition for Backtrack-Free Search
Journal of the ACM (JACM)
Excluding Symmetries in Constraint-Based Search
Constraints
JELIA '96 Proceedings of the European Workshop on Logics in Artificial Intelligence
Excluding Symmetries in Constraint-Based Search
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
Fast, Constraint-Based Threading of HP-Sequences to Hydrophobic Cores
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
An Upper Bound for Number of Contacts in the HP-Model on the Face-Centered-Cubic Lattice (FCC)
COM '00 Proceedings of the 11th Annual Symposium on Combinatorial Pattern Matching
Optimally Compact Finite Sphere Packings - Hydrophobic Cores in the FCC
CPM '01 Proceedings of the 12th Annual Symposium on Combinatorial Pattern Matching
Protein Decoy Generation Using Branch and Bound with Efficient Bounding
WABI '08 Proceedings of the 8th international workshop on Algorithms in Bioinformatics
DFS Based Partial Pathways in GA for Protein Structure Prediction
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
Logic Programming Techniques in Protein Structure Determination: Methodologies and Results
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Protein structure prediction on the face centered cubic lattice by local search
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
International Journal of Data Mining and Bioinformatics
Clp-based protein fragment assembly*
Theory and Practice of Logic Programming
Effect of sequences on the shape of protein energy landscapes
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
Twin Removal in Genetic Algorithms for Protein Structure Prediction Using Low-Resolution Model
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
A constraint programming approach to bioinformatics structural problems
PADL'07 Proceedings of the 9th international conference on Practical Aspects of Declarative Languages
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
Cross-lattice behavior of general ACO folding for proteins in the HP model
Proceedings of the 28th Annual ACM Symposium on Applied Computing
A multiple minima genetic algorithm for protein structure prediction
Applied Soft Computing
A constraint solver for flexible protein models
Journal of Artificial Intelligence Research
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Simplified protein models are used for investigating general properties of proteins and principles of protein folding. Furthermore, they are suited for hierarchical approaches to protein structure prediction. A well known protein model is the HP-model of Lau and Dill [Lau, K. F., & Dill, K. A. (1989)]. A lattice statistical mechanics model of the conformational and sequence spaces of proteins. Macromolecules, 22, 3986---3997) which models the important aspect of hydrophobicity. One can define the HP-model for various lattices, among them two-dimensional and three-dimensional ones. Here, we investigate the three-dimensional case. The main motivation for studying simplified protein models is to be able to predict model structures much more quickly and more accurately than is possible for real proteins. However, up to now there was a dilemma: the algorithmically tractable, simple protein models can not model real protein structures with good quality and introduce strong artifacts.We present a constraint-based method that largely improves this situation. It outperforms all existing approaches for lattice protein folding in HP-models. This approach is the first one that can be applied to two three-dimensional lattices, namely the cubic lattice and the face-centered-cubic (FCC) lattice. Moreover, it is the only exact method for the FCC lattice. The ability to use the FCC lattice is a significant improvement over the cubic lattice. The key to our approach is the ability to compute maximally compact sets of points (used as hydrophobic cores), which we accomplish for the first time for the FCC lattice.