Protein Structure from Contact Maps: A Case-Based Reasoning Approach
Information Systems Frontiers
Review: Protein knots and fold complexity: Some new twists
Computational Biology and Chemistry
International Journal of Bioinformatics Research and Applications
Improving the prediction of helix-residue contacts in all-alpha proteins
NN'08 Proceedings of the 9th WSEAS International Conference on Neural Networks
A Demonstration of Clustering in Protein Contact Maps for Alpha Helix Pairs
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Prediction of inter-residue contact clusters from hydrophobic cores
International Journal of Data Mining and Bioinformatics
Bayesian Models and Algorithms for Protein β-Sheet Prediction
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A consensus approach to predicting protein contact map via logistic regression
ISBRA'11 Proceedings of the 7th international conference on Bioinformatics research and applications
Protein contact map prediction using multi-stage hybrid intelligence inference systems
Journal of Biomedical Informatics
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Motivation: Despite the continuing advance in the experimental determination of protein structures, the gap between the number of known protein sequences and structures continues to increase. Prediction methods can bridge this sequence--structure gap only partially. Better predictions of non-local contacts between residues could improve comparative modeling, fold recognition and could assist in the experimental structure determination. Results: Here, we introduced PROFcon, a novel contact prediction method that combines information from alignments, from predictions of secondary structure and solvent accessibility, from the region between two residues and from the average properties of the entire protein. In contrast to some other methods, PROFcon predicted short and long proteins at similar levels of accuracy. As expected, PROFcon was clearly less accurate when tested on sparse evolutionary profiles, that is, on families with few homologs. Prediction accuracy was highest for proteins belonging to the SCOP alpha/beta class. PROFcon compared favorably with state-of-the-art prediction methods at the CASP6 meeting. While the performance may still be perceived as low, our method clearly pushed the mark higher. Furthermore, predictions are already accurate enough to seed predictions of global features of protein structure. Availability: http://www.predictprotein.org/submit_profcon.html Contact: punta@cubic.bioc.columbia.edu Supplementary information: http://www.rostlab.org/results/2005/profcon