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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

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Versioning


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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 in publications

 (11)
PMCID: 5938574
PMID: 29618526
DOI: 10.1098/rsif.2017.0387

[…] 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 […]

PMCID: 5870574
PMID: 28881974
DOI: 10.1093/bioinformatics/btx239

[…] families. to what extent these predictions can be used to produce accurate models of the families is not known., results: we present the pconsfold2 pipeline that uses contact predictions from pconsc3, the confold folding algorithm and model quality estimations to predict the structure of a protein. we show that the model quality estimation significantly increases the number of models […]

PMCID: 5414403
PMID: 28512576
DOI: 10.1107/S2052252517005115

[…] 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 […]

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

[…] default parameters. the final secondary structure used for further analyses was determined using a majority voting approach on the output of each algorithm., 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 […]

PMCID: 5114557
PMID: 27857150
DOI: 10.1038/srep36679

[…] (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 […]


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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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