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PconsC specifications

Information


Unique identifier OMICS_03522
Name PconsC
Software type Application/Script
Interface Graphical user interface
Restrictions to use None
Input data An amino acid sequence.
Input format FASTA
Operating system Unix/Linux
License GNU General Public License version 2.0
Computer skills Medium
Stability Stable
Requirements
h5py, Cython, Julie interpreter, Pyhton, CD-HIT
Maintained Yes

Download


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Versioning


No version available

Maintainer


  • person_outline Arne Elofsson

Additional information


PconsC2 is available https://github.com/ElofssonLab/web_pconsc2 PconsC3 is available at http://pconsc3.bioinfo.se/pred/ and PconsC4 is available at https://github.com/ElofssonLab/PconsC4

Information


Unique identifier OMICS_03522
Name PconsC
Interface Web user interface
Restrictions to use None
Input data An amino acid sequence.
Input format FASTA
License GNU General Public License version 3.0
Computer skills Basic
Version 3.0
Stability Stable
Maintained Yes

Maintainer


  • person_outline Arne Elofsson

Additional information


PconsC2 is available https://github.com/ElofssonLab/web_pconsc2 PconsC3 is available at http://pconsc3.bioinfo.se/pred/ and PconsC4 is available at https://github.com/ElofssonLab/PconsC4

Publications for PconsC

PconsC citations

 (11)
library_books

Opportunities and obstacles for deep learning in biology and medicine

2018
PMCID: 5938574
PMID: 29618526
DOI: 10.1098/rsif.2017.0387

[…] eins with few sequence homologues, but their accuracy is still far from satisfactory. In recent years, deeper architectures have been explored for contact prediction, such as CMAPpro [], DNCON [] and PConsC []. However, blindly tested in the well-known CASP competitions, these methods did not show any advantage over MetaPSICOV [].Recently, Wang et al. [] proposed the deep learning method RaptorX-C […]

call_split

Large scale structure prediction by improved contact predictions and model quality assessment

2017
Bioinformatics
PMCID: 5870574
PMID: 28881974
DOI: 10.1093/bioinformatics/btx239
call_split See protocol

[…] PconsC3 is used to predict contacts between pairs of amino acids in the Pfam reference sequences. To overcome the limit of DCA methods requiring large alignments, PconsC3 combines the results of such […]

library_books

Applications of contact predictions to structural biology

2017
PMCID: 5414403
PMID: 28512576
DOI: 10.1107/S2052252517005115

[…] ng GREMLIN (Ovchinnikov, Kinch et al., 2015), or the output of multiple EC methods along with sequence profiles can be used as features in SML methods, for example MetaPSICOV (Jones et al., 2015) and PconsC2 (Skwark et al., 2014). Pipelines combining various EC and SML methods are often referred to as metapredictors, and a useful comparison of the best methods has recently been published (Wang et […]

library_books

A Biologically validated HCV E1E2 Heterodimer Structural Model

2017
Sci Rep
PMCID: 5428263
PMID: 28303031
DOI: 10.1038/s41598-017-00320-7

[…] Six EC algorithms (metaPSICOV, ccmPRED, PConsC2, plmDCA, EPC-MAP and RaptorX) were selected to predict all possible E1E2 residue couples’ propensity of interaction, –. When possible, the algorithm was fed with the refined E1E2 alignment (pl […]

library_books

Observation selection bias in contact prediction and its implications for structural bioinformatics

2016
Sci Rep
PMCID: 5114557
PMID: 27857150
DOI: 10.1038/srep36679

[…] nces (r = 0.70) on 150 proteins sampled from the STRUCT dataset. This confirms the previously determined correlation between available evolutionary information and CP performances for plmDCA, PSICOV, PconsC and PconsC2 on the PSICOV dataset.These results question the consistency of the accuracy that CP methods claim, since their published performances are calculated on protein datasets that are si […]

call_split

Comparing co evolution methods and their application to template free protein structure prediction

2016
Bioinformatics
PMCID: 5860252
PMID: 28171606
DOI: 10.1093/bioinformatics/btw618
call_split See protocol

[…] ents has been identified as a crucial step for predicting contacts (). To ensure consistency in our analyses, the same alignment has been used as input for all contact predictors, the exception being PConsC2 (for more details, refer to Section 2.3). The multiple sequence alignment (MSA) was computed according to the following parameters: HHBlits version 2.0.15 June 2012Database: Uniprot20_2013_03I […]

Citations

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PconsC institution(s)
Science for Life Laboratory and Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
PconsC funding source(s)
Supported by grants from the Swedish Research Council (VR-NT 2016-03798).

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