Pcons5: combining consensus, structural evaluation and fold recognition scores

By Björn Wallner, Arne Elofsson. 2005

104 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Arne Elofsson
2. Yang Zhang
3. Björn Wallner
4. Janusz M. Bujnicki
5. David Ménendez Hurtado
6. G. Bunkoczi
7. John Lamb
8. Mirco Michel

In Materials Chemistry

1. Yang Zhang
2. Björn Wallner
3. Arne Elofsson
4. Sitao Wu
5. David Ménendez Hurtado
6. Liam J. McGuffin
7. G. Bunkoczi
8. Karolis Uziela

In Molecular Biology

1. Yang Zhang
2. Arne Elofsson
3. Björn Wallner
4. Liam J. McGuffin
5. David Ménendez Hurtado
6. Sitao Wu
7. Karolis Uziela
8. Mirco Michel

Citations in the corpus

• Local Error Estimates Dramatically Improve the Utility of Homology Models for Solving Crystal Structures by Molecular Replacement (2015, methodology): “Prediction of Coordinate Errors In principle, there are two strategies to obtain coordinate error estimates in a model; one using consensus (Wallner and Elofsson, 2005) and one using information only from the model itself, i.”
• LOMETS: A local meta-threading-server for protein structure prediction (2007, methodology): “As a control, we also downloaded the PCONS5, the newest version of PCONS meta-server selection program by Wallner and Elofsson (34), which combines consensus analysis (by LGscore), structural evaluation and inherent score of threading servers.”
• Limits and potential of combined folding and docking (2021, background): “These types of quality estimates have been successful in CASP since CASP5[40,41].”
• Large-scale structure prediction by improved contact predictions and model quality assessment (2017, methodology): “Here, we have used the Pcons consensus method to predict a quality score for each model based on a comparison of all models against each other (consensus method) (Wallner and Elofsson, 2005b).”
• pyconsFold: a fast and easy tool for modeling and docking using distance predictions (2021, methodology): “By default the generated models are ranked by CNS internal NOE energy, but Quality Assessment score pcons (Wallner and Elofsson, 2005) will also be calculated.”
• MetaDisorder: a meta-server for the prediction of intrinsic disorder in proteins (2012, methodology): “…run in two different modes (with and without masking regions with low sequence complexity) over the culled PDB database [37], PHYRE [38], and PCONS [39] (a consensus method that uses as an input models generated by MODELLER [40] based on alignments from the previously mentioned fold-recognition…”
• Improved model quality assessment using ProQ2 (2012, methodology): “Finally, there are also hybrid methods that combine the singlemodel and consensus approaches to achieve improved performance [21-24].”