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Citations per year

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Popular tool citations

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ProQ3D specifications

Information


Unique identifier OMICS_14652
Name ProQ3D
Alternative name ProQ3
Interface Web user interface
Restrictions to use None
Input data Structure models in PDB format, the amino acid target sequence in FASTA format
Input format PDB, FASTA
Output data The global and local scores of the models to be predicted
Output format TXT, ZIP
Programming languages Python, R
Computer skills Basic
Stability Stable
Maintained Yes

Documentation


Maintainers


  • person_outline Arne Elofsson
  • person_outline Nanjiang Shu
  • person_outline David Menendez Hurtado

Information


Unique identifier OMICS_14652
Name ProQ3D
Alternative name ProQ3
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data Structure models in PDB format, the amino acid target sequence in FASTA format.
Input format PDB, FASTA
Output data The global and local scores of the models to be predicted.
Output format TXT, ZIP
Operating system Unix/Linux
Programming languages Python, R
Computer skills Advanced
Stability Stable
Requirements
Rosetta, zoo, EMBOSS, numpy, h5py, keras
Maintained Yes

Download


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Versioning


No version available

Documentation


Maintainers


  • person_outline Arne Elofsson
  • person_outline Nanjiang Shu
  • person_outline David Menendez Hurtado

Publications for ProQ3D

ProQ3D citations

 (3)
library_books

Predictive and Experimental Approaches for Elucidating Protein–Protein Interactions and Quaternary Structures

2017
Int J Mol Sci
PMCID: 5751226
PMID: 29206185
DOI: 10.3390/ijms18122623

[…] manageable number and processed manually to determine the highest quality predicted pose., although many different forms of tertiary model evaluation exist; such as those implemented in modfold6 [], proq3 [,] and others [], recent progression onto quaternary protein modelling means that a reliable generic quaternary structure model quality assessment method has yet to be developed. the zdock […]

library_books

An overview of comparative modelling and resources dedicated to large scale modelling of genome sequences

2017
Acta Crystallogr D Struct Biol
PMCID: 5571743
PMID: 28777078
DOI: 10.1107/S2059798317008920

[…] combines evolutionary information, multiple sequence alignment data and structural features from the model using a support vector machine (svm) to assess the quality (ray et al., 2012). the recent proq3 uses a deep-learning method to combine proq2 with rosetta energy terms (leaver-fay et al., 2011) and has been shown to be superior to proq2 (uziela et al., 2016, 2017). deepqa is another […]

library_books

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

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

[…] pipeline is the model quality assessment. in addition to existing model quality assessment methods, we introduce pcombc. pcombc is a linear combination of three separate assessment scores: pcons (), proq3d () and the agreement between predicted and observed contacts in the model., finally, we apply pconsfold2 to 6379 pfam families without a known structure. using the cutoffs for a false positive […]


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ProQ3D institution(s)
Department of Biochemistry and Biophysics and Science for Life Laboratory, Stockholm University, Solna, Sweden; Bioinformatics Short-term Support and Infrastructure (BILS), Science for Life Laboratory, Solna, Sweden; Department of Physics, Chemistry and Biology (IFM) /Bioinformatics, Linkoping University, Linkoping, Sweden
ProQ3D funding source(s)
Supported by grants from the Swedish Research Council (VR-NT 2016-03798 and 2012-5270) and Swedish e-Science Research Center.

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