NEWS ! Pcons-meta server
Now you can run Pcons from our local meta-server. It offers
several advantages over the other servers that use Pcons. Try
Pcons a consensus fold recognition predictor
Pcons was the first consensus server for fold recognition. It
selects the best prediction out of several predictions. For
each query sequence predictions from several fold recognition
servers is collected. For each of these models a measure that
relates to the quality of the model is calculated. The
prediction of this new measure is accomplished by utilizing
structural comparisons between the models and analyzing the
server score for a particular model. Pcons makes at least 10%
more correct predictions than the best single method and the
specificity is significantly better.
Different Pcons version
Since the development of Pcons-1 during fall 2000 we have
developed 4 new versions. The differences between them will
shortly be described below.
- Pcons-1: Used 5 different servers and a Neural
network to predict the quality. It was trained using
LiveBench-1 data and tested in
LiveBench-2. Pcons-1 is now canceled.
- Pcons-2: Used 7 different servers and a linear
regression to predict the quality. Quality was measured using
an updated version of LGscore. It
was trained using LiveBench-2 data and tested in CASP5, CAFASP3 and LiveBench-6. It is also
the bases for Pmodeller.
- Pcons-3: Used 3, i.e. fewer, different servers and
a simplified method to measure similarity between models. It
was trained on LiveBench-4 data. Due to
problems with ShotGun models and Pmodeller (see below)
Pcons-3 is now canceled.
- Pcons-4Due to problems with "ShotGun" models
Pcons-3 was replaced by Pcons-4 and uses 4 different
servers. It was also trained on LiveBench-4 data.
- Pcons-5: Developed after CASP5 and made to be more
flexible, i.e. easier to upgrade. It uses a variable number of
servers + information from a structural evaluation of the
models using a C-alpha based version of ProQ.
Pmodeller vs Pcons
Pmodeller is an addition on top of
Pcons. In Pmodeller all atom models are built, and also
evaluated using ProQ. It has been
shown in CASP5 that Pmodeller works better than
Pcons. Currently Pmodeller (based on Pcons-2) and Pmodeller-4
(based on Pcons-4) is used. To use it you need a valid license
Pmodeller-5 is still being developed as Pcons-5 includes the
ProQ evaluation by itself.
Pcons6 and Pmodeller-6 has been tested.
You can submit a sequence to Pcons using meta servers either at
Last modified: Fri Jan 19 10:34:10 CET 2007
- http://bioinfo.pl Pcons II, IV and V
- http://genesilico.pl Pcons II and V
- Now we have an official meta-server available at www.cbr.su.se it uses
Pcons-V, ProQ and other methods that we developed for
- Submit a sequence to
- If you use Pcons please cite:
- Lundström J, Rychlewski L, Bujnicki
J, Elofsson A. Pcons: A neural-network-based consensus
predictor that improves fold recognition. Protein Sci. 2001
- "Automatic consensus based fold recognition using
Pcons, ProQ and Pmodeller." Björn Wallner, Huisheng
Fang and Arne Elofsson, Proteins 2003 53(S6):534-541 pdf
- Björn Wallner and Arne Elofsson "Pcons5: combining
consensus, structural evaluation and fold recognition scores",
Bioinformatics 2005 21(23):4248-54. pdf
- Here is a Paper describing Pcons 2
- LiveBench a
continuous benchmarking of fold recognition methods (including
- What is a significant Pcons score ?
Any score higher than 1.5 should be significant