EVAcon: a protein contact prediction evaluation service
نویسندگان
چکیده
منابع مشابه
EVAcon: a protein contact prediction evaluation service
Here we introduce EVAcon, an automated web service that evaluates the performance of contact prediction servers. Currently, EVAcon is monitoring nine servers, four of which are specialized in contact prediction and five are general structure prediction servers. Results are compared for all newly determined experimental structures deposited into PDB ( approximately 5-50 per week). EVAcon allows ...
متن کاملEvolutionary Protein Contact Maps Prediction
In this study, a novel residue-residue contacts prediction approach based on evolutionary computation is presented. The prediction is based on four amino acids properties. In particular, we consider the hydrophobicity, the polarity, the charge and size of residues of amino acids. The prediction model consists of a set of rules that identifies contacts between amino acids. Results obtained confi...
متن کاملCoinFold: a web server for protein contact prediction and contact-assisted protein folding
CoinFold (http://raptorx2.uchicago.edu/ContactMap/) is a web server for protein contact prediction and contact-assisted de novo structure prediction. CoinFold predicts contacts by integrating joint multi-family evolutionary coupling (EC) analysis and supervised machine learning. This joint EC analysis is unique in that it not only uses residue coevolution information in the target protein famil...
متن کاملProtein contact prediction using patterns of correlation.
We describe a new method for using neural networks to predict residue contact pairs in a protein. The main inputs to the neural network are a set of 25 measures of correlated mutation between all pairs of residues in two "windows" of size 5 centered on the residues of interest. While the individual pair-wise correlations are a relatively weak predictor of contact, by training the network on win...
متن کاملDeep architectures for protein contact map prediction
MOTIVATION Residue-residue contact prediction is important for protein structure prediction and other applications. However, the accuracy of current contact predictors often barely exceeds 20% on long-range contacts, falling short of the level required for ab initio structure prediction. RESULTS Here, we develop a novel machine learning approach for contact map prediction using three steps of...
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ژورنال
عنوان ژورنال: Nucleic Acids Research
سال: 2005
ISSN: 0305-1048,1362-4962
DOI: 10.1093/nar/gki411