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CONSENSUS FOLD RECOGNITION BY PREDICTED MODEL QUALITY

JINBO XU, LIBO YU, MING LI
2005 Proceedings of the 3rd Asia-Pacific Bioinformatics Conference  
The consensus method was first applied in fold recognition by some individual servers  ...  Our SVM model extracts the features from a predicted structural model by comparing it to other models generated by all the individual servers and then predicts the quality of this model.  ...  Our research is supported by the National Science and Engineering Research Council of Canada, CITO's Champion of Innovation Program, the Killam Fellowship, Canada Research Chair Program, and the Human  ... 
doi:10.1142/9781860947322_0008 fatcat:jdtijdpdtndkfgwifllylinfli

Automatic consensus-based fold recognition using Pcons, ProQ, and Pmodeller

Bj�rn Wallner, Huisheng Fang, Arne Elofsson
2003 Proteins: Structure, Function, and Bioinformatics  
Furthermore we show that the inclusion of another novel method, ProQ 2 , to evaluate the quality of the protein models improves the predictions. Proteins 2003;53:534 -541.  ...  Therefore, the success of Pmodeller and other consensus servers should be seen as a tribute to the collective of all developers of fold recognition servers.  ...  The success of Pmodeller and other consensus-based methods should really be attributed to the whole collective force of fold recognition method developers.  ... 
doi:10.1002/prot.10536 pmid:14579343 fatcat:boyhoa3b4ne3fnjv77ugnxri2i

'Meta'Approaches to Protein Structure Prediction [chapter]

Janusz M. Bujnicki, Daniel Fischer
2008 Nucleic acids and molecular biology  
The consensus predictions were obtained by analyzing the predictions of the fold-recognition servers that participated in the parallel CAFASP2 experiment.  ...  PMOD uses MODELLER (Sali and Blundell 1993) to generate full-atom models based on the selection of fold-recognition results reported by PCONS, amended by secondary structure predicted by PSI-PRED (Jones  ... 
doi:10.1007/978-3-540-74268-5_2 fatcat:e3dwvh2nsfholik5ptowgnilfy

Benchmarking consensus model quality assessment for protein fold recognition

Liam J McGuffin
2007 BMC Bioinformatics  
Results: The ModSSEA method is found to be an effective model quality assessment program for ranking multiple models from many servers, however further accuracy can be gained by using the consensus approach  ...  Several of the true MQAPs are also shown to add value to most individual fold recognition servers by improving model selection, when applied as a post filter in order to re-rank models.  ...  Acknowledgements This work was supported by a Research Councils United Kingdom (RCUK) Academic Fellowship.  ... 
doi:10.1186/1471-2105-8-345 pmid:17877795 pmcid:PMC2048972 fatcat:2jlp5g4z6jhnjmlubbadpxemmq

Pcons5: combining consensus, structural evaluation and fold recognition scores

B. Wallner, A. Elofsson
2005 Bioinformatics  
Pcons5 integrates information from three different sources: the consensus analysis, structural evaluation and the score from the fold recognition servers.  ...  Motivation: The success of the consensus approach to the protein structure prediction problem has led to development of several different consensus methods.  ...  ACKNOWLEDGEMENTS This work was supported by grants from the Swedish Natural Sciences Research Council and by a grant from the Graduate Research School in Genomics and Bioinformatics.  ... 
doi:10.1093/bioinformatics/bti702 pmid:16204344 fatcat:uw7ruenuwzfydbuccj7czrpnr4

Pcons: A neural-network-based consensus predictor that improves fold recognition

Jesper Lundström, Leszek Rychlewski, Janusz Bujnicki, Arne Elofsson
2008 Protein Science  
During recent years many protein fold recognition methods have been developed, based on different algorithms and using various kinds of information.  ...  Pcons attempts to select the best model out of those produced by six prediction servers, each using different methods.  ...  For each fold recognition server a primary neural network layer was trained to predict the quality of a model based on the confidence score reported by the server and the fraction of other similar models  ... 
doi:10.1110/ps.08501 pmid:11604541 pmcid:PMC2374055 fatcat:42qc4mbqlzhezgick7vmanur7m

Pcons.net: protein structure prediction meta server

B. Wallner, P. Larsson, A. Elofsson
2007 Nucleic Acids Research  
The Pcons.net Meta Server (http://pcons.net) provides improved automated tools for protein structure prediction and analysis using consensus.  ...  For more difficult targets the sequence is automatically submitted to publicly available fold-recognition servers that use more advanced approaches to find distant structural homologs.  ...  The 46 h time limit is set to allow for as many fold-recognition servers as possible to finish and provide the basis for the consensus analysis.  ... 
doi:10.1093/nar/gkm319 pmid:17584798 pmcid:PMC1933226 fatcat:pu2ovy6zxndrhkwx66fcjm7sva

3D-Jury: a simple approach to improve protein structure predictions

K. Ginalski, A. Elofsson, D. Fischer, L. Rychlewski
2003 Bioinformatics  
The algorithm resembles methods of selecting models generated using ab initio folding simulations.  ...  Motivation: Consensus structure prediction methods (meta-predictors) have higher accuracy than individual structure prediction algorithms (their components).  ...  This addition is likely to boost the quality of the predictions.  ... 
doi:10.1093/bioinformatics/btg124 pmid:12761065 fatcat:cqnwsbwiubfcvd2xvigmh5qc7e

GeneSilico protein structure prediction meta-server

M. A. Kurowski
2003 Nucleic Acids Research  
Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail.  ...  Foldrecognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed.  ...  ACKNOWLEDGEMENTS We are grateful to developers of the protein fold recognition servers who kindly agreed to have them included in our metaserver, in particular Drs Arne Elofsson, Daniel  ... 
doi:10.1093/nar/gkg557 pmid:12824313 pmcid:PMC168964 fatcat:fryudy4xejaslg3mja7s37lxku

Assessment of the CASP4 fold recognition category

Manfred J. Sippl, Peter Lackner, Francisco S. Domingues, Andreas Prli?, Rainer Malik, Antonina Andreeva, Markus Wiederstein
2001 Proteins: Structure, Function, and Bioinformatics  
The 125 fold recognition groups were assessed by a total score that summarizes their performance over all targets and a quality score reflecting the average quality of the submitted models.  ...  We present the assessment of the CASP4 fold recognition category.  ...  CM: comparative modeling; CM/FR: comparative modeling/fold recognition; FR/H: fold recognition homologous; FR/A: fold recognition analogous; FR/NF: fold recognition/new fold; NF: new fold.  ... 
doi:10.1002/prot.10006 pmid:11835482 fatcat:h6kmbliuundsfklh4p6z4gie4m

Contact prediction in protein modeling: Scoring, folding and refinement of coarse-grained models

Dorota Latek, Andrzej Kolinski
2008 BMC Structural Biology  
The most relevant were nonlocal contact predictions for targets from the most difficult categories: fold recognition-analogy and new fold.  ...  According to our results, the best performing were the contacts with the accuracy balanced with the coverage, obtained either from the best two predictors only or by a consensus from as many predictors  ...  This seems to be especially useful in the structure modeling of new folds, for which meta-predictors (Bioinfo [22] etc.) based on the consensus of fold recognition methods do not yield any reliable templates  ... 
doi:10.1186/1472-6807-8-36 pmid:18694501 pmcid:PMC2527566 fatcat:uvx7r52otzcrlar7ij6wyrlrq4

A Deeply Glimpse into Protein Fold Recognition

Marwa Mohammed M. Ghareeb, Ahmed Sharaf Eldin, Taysir Hassan A. Soliman, Mohammed Ebrahim Marie
2013 Zenodo  
Thus, the need of extracting structural information through computational analysis of protein sequences has become very important, especially, the prediction of the fold of a query protein from its primary  ...  SVM first extracts the features of a structural model by comparing the model to the other models produced by all the individual servers. Then, the SVM predicts the quality of each model.  ...  Pcons used a set of neural networks to predict the quality and accuracy of the collected models. Pcons was specifically trained to predict the quality of the final models.  ... 
doi:10.5281/zenodo.3348233 fatcat:sui7cakaaraqdh2a6pifgzrdmm

Critically assessing the state-of-the-art in protein structure prediction

D T Jones
2001 The Pharmacogenomics Journal  
One of the most tantalising 'grand challenges' in structural biology is to solve the problem of predicting the structure of a protein from its amino acid sequence alone.  ...  Although this problem appeals to many researchers on a purely academic level, the practical importance of protein structure prediction has become particularly clear with the release of the first draft  ...  (and hence the 3-D models) are of very poor quality.  ... 
doi:10.1038/sj.tpj.6500017 pmid:11911439 fatcat:ydcrksyq3rcb5lyxisy23x77c4

Use of structure comparison methods for the refinement of protein structure predictions. I. Identifying the structural family of a protein from low-resolution models

Xavier de la Cruz, Ian Sillitoe, Christine Orengo
2001 Proteins: Structure, Function, and Bioinformatics  
In the present article, we address the problem of obtaining better-quality predictions, starting from lowresolution models.  ...  In general, we found that for predictions with a resolution of >5-7 Å, structure comparison methods were able to identify the fold of a protein in the top positions. Proteins 2002;46:72-84.  ...  Fig. 1 . 1 Schematic demonstrating the fold recognition procedure using predicted structures.  ... 
doi:10.1002/prot.10002 pmid:11746704 fatcat:iqixixpjxzhmnadd6l2rz53xrm

3D-SHOTGUN: A novel, cooperative, fold-recognition meta-predictor

Daniel Fischer
2003 Proteins: Structure, Function, and Bioinformatics  
The input to 3D-SHOTGUN are the top models predicted by a number of independent fold-recognition servers.  ...  In particular, fold-recognition methods aim to predict approximate 3D models for proteins bearing no sequence similarity to any protein of known structure.  ...  ACKNOWLEDGMENTS 3DS3 and 3DS5 could not exist without the availability of the initial model-generating servers; our thanks to their developers.  ... 
doi:10.1002/prot.10357 pmid:12696054 fatcat:gittw6iq7rgxfk3iavgcsj472u
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