Biomedical subjects

Michael Tress

Publications and source records attributed to Michael Tress.

4 recordsLinked to original sources

PubMed2006

TreeDet: a web server to explore sequence space.

The TreeDet (Tree Determinant) Server is the first release of a system designed to integrate results from methods that predict functional sites in protein families. These methods take into account the relation between sequence conservation and evolutionary importance. TreeDet fully analyses the space of protein sequences in either user-uploaded or automatically generated multiple sequence alignments. The methods implemented in the server represent three main classes of methods for the detection of family-dependent conserved positions, a tree-based method, a correlation based method and a method that employs a principal component analyses coupled to a cluster algorithm. An additional method is provided to highlight the reliability of the position in the alignments. The server is available at http://www.pdg.cnb.uam.es/servers/treedet.

Amino Acid Sequence↗

PubMed2005

Scoring docking models with evolutionary information.

We have developed methods for the extraction of evolutionary information from multiple sequence alignments for use in the study of the evolution of protein interaction networks and in the prediction of protein interaction. For Rounds 3, 4, and 5 of the CAPRI experiment, we used scores derived from the analysis of multiple sequence alignments to submit predictions for 7 of the 12 targets. Our docking models were generated with Hex and GRAMM, but all our predictions were selected using methods based on multiple sequence alignments and on the available experimental evidence. With this approach, we were able to predict acceptable level models for 4 of the targets, and for a fifth target, we located the residues involved in the binding surface. Here we detail our successes and highlight several of the limitations and problems that we faced while dealing with particular docking cases.

Algorithms↗

PubMed2005

Domain definition and target classification for CASP6.

Assessment of structure predictions in CASP6 was based on single domains isolated from experimentally determined structures, which were categorized into comparative modeling, fold recognition, and new fold targets. Domain definitions were defined upon visual examination of the structures with the aid of automated domain-parsing programs. Domain categorization was determined by comparison of the target structures with those in the Protein Data Bank at the time each target expired and a variety of sequence and structure-based methods to determine potential homologous relationships.

Amino Acid Sequence↗

PubMed2005

Assessment of predictions submitted for the CASP6 comparative modeling category.

Here we present a full overview of the Critical Assessment of Protein Structure Prediction (CASP6) comparative modeling category. Prediction accuracy for the 43 comparative modeling targets was assessed through detailed numerical comparisons between predicted and experimental structures. Assessments using standard measures for model backbone quality and structural alignment accuracy highlighted a small number of groups with stand out predictions and these findings were backed up by statistical comparisons. We were able to carry out evaluations of side-chain contacts predictions and side-chain rotamer accuracy, for which one group turned out to have statistically better predictions. We also assessed the prediction quality of structurally divergent regions and biologically important sites. Interestingly we were able to show that predictors were not predicting these important functional regions with any greater accuracy than the rest of the structure. In addition we investigated the ability of predictors to build models that improve on the structural template and reached some tentative conclusions from comparisons with the previous CASP experiment.

Algorithms↗