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Protocols

CCMpred specifications

Information


Unique identifier OMICS_05287
Name CCMpred
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C
Parallelization CUDA
License GNU Affero General Public License version 3
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Documentation


Maintainer


  • person_outline Johannes Söding

Publication for CCMpred

CCMpred citations

 (10)
library_books

Approaches to ab initio molecular replacement of α helical transmembrane proteins

2017
Acta Crystallogr D Struct Biol
PMCID: 5713875
PMID: 29199978
DOI: 10.1107/S2059798317016436

[…] Solution was then attempted with models built with the assistance of contact predictions from CCMPRED, MEMBRAIN or METAPSICOV_S1. The results are summarized in Fig. 1, with graphical summaries of the results shown in Supplementary Figs. S8, S10 and S12, and analyses of the TM scores shown in S […]

library_books

Improved protein contact predictions with the MetaPSICOV2 server in CASP12

2017
Proteins
PMCID: 5836854
PMID: 28901583
DOI: 10.1002/prot.25379

[…] taPSICOV method to derive covariation‐based contacts (Jones et al. ). At its core MetaPSICOV is a meta‐predictor based on different covariation prediction algorithms, including mfDCA (Kaján et al. ), CCMpred (Seemayer et al. ) and PSICOV (Jones et al. ). When there isn't sufficient sequence data available to allow effective covariation analysis, the neural network is able to exploit information fr […]

library_books

A Biologically validated HCV E1E2 Heterodimer Structural Model

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

[…] selected to predict all possible E1E2 residue couples’ propensity of interaction, –. When possible, the algorithm was fed with the refined E1E2 alignment (plmDCA), while metaPSICOV, PConsC2, EPC-MAP, ccmPRED and RaptorX web servers received the single H77 E1E2 sequence. In order to select the algorithm that reached the best performance for E1E2, predicted contact maps were compared to the real con […]

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

[…] riment in which we artificially cut the sizes of the MSAs collected for PSICOV dataset in order to match the number of homologs available for NOUMENON. We then computed the performances of PSICOV and CCMpred predictors on this version of PSICOV dataset with these artificially reduced number of homologs: PSICOV yielded to a best L mean precision of 0.20 and CCMpred of 0.27 (see ). Artificially redu […]

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

[…] predictors avoids the approximation of the inverse covariance matrix altogether by maximizing a pseudo-likelihood. For the analyses described in this work, we have used two implementations of plmDCA: CCMPred v0.1.0 with standard parameters () and GREMLIN v2.01 with standard parameters ().PConsC uses different sets of contact predictions output by PSICOV and plmDCA (standard parameters are used for […]

library_books

Potential DNA binding and nuclease functions of ComEC domains characterized in silico

2016
Proteins
PMCID: 5031224
PMID: 27318187
DOI: 10.1002/prot.25088

[…] ckhmmer against the UniRef100 database or HHblits v2.0.15 against the non‐redundant UniProt20 database v2013.03 at E‐value cutoffs of 10−40, 10−10, 10−4, and 1. bbcontacts was applied to results from CCMpred, working with the results of an HHblits v2.0.15 database search of UniProt20 database v2013.03 with an E‐value cutoff of 10−3 and filtering to 90% sequence identity using HHfilter v2.0.15 to r […]


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CCMpred institution(s)
Gene Center, LMU Munich, Munich; Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
CCMpred funding source(s)
This work was funded by the Deutsche Forschungsgemeinschaft (Grants GRK1721 and SFB646) and the Bavarian Center for Molecular Biosystems (BioSysNet).

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