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UCON specifications

Information


Unique identifier OMICS_20061
Name UCON
Alternative name Unstructured regions through CONtact maps
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Maintained Yes

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Versioning


No version available

Maintainer


  • person_outline Avner Schlessinger

Additional information


This program can also be accessed via the PredictProtein service.

Publication for Unstructured regions through CONtact maps

UCON citations

 (6)
library_books

Discovery of numerous novel small genes in the intergenic regions of the Escherichia coli O157:H7 Sakai genome

2017
PLoS One
PMCID: 5597208
PMID: 28902868
DOI: 10.1371/journal.pone.0184119

[…] This software predicts structural and functional features of the putative proteins. The results of PROFphd (secondary structure) [], TMSEG (transmembrane helices) [], DISULFIND (disulfide bonds) [], UCON (disordered regions) [] and LocTree3 (subcellular localization) [] were analyzed in further detail. […]

library_books

Translatomics combined with transcriptomics and proteomics reveals novel functional, recently evolved orphan genes in Escherichia coli O157:H7 (EHEC)

2016
BMC Genomics
PMCID: 4765031
PMID: 26911138
DOI: 10.1186/s12864-016-2456-1

[…] own proteins, []), SEG (low- and high-complexity regions, []), ConSurf (evolutionary conservation of amino acids, []), DISULFIND (disulfide bonds, []). For disordered region predictions, PROFbval [], UCON [] and METADISORDER [] were used. Further, PROFtmb (bacterial transmembrane β-barrels, []), Metastudent (Gene Ontology terms, []), and LocTree3 (subcellular localization, []) were applied. Signal […]

library_books

MFDp2

2013
PMCID: 5424793
PMID: 28516009
DOI: 10.4161/idp.24428

[…] ared with the second suggested threshold that optimizes the Sw measure), SPINE-D, two versions of CSpritz (CSpritz Long and CSpritz Short), MFDp, PONDRFIT, MD, PreDisorder, DISOCLUST, PrDos, NORSnet, UCON, two versions of IUPred (IUPred Long and IUPred Short), PROFBVAL and DISOPRED2. PROFBVAL is designed to predict b-factors of residues, which are different than propensity for disorder; however, t […]

library_books

In silico prediction of disorder content using hybrid sequence representation

2011
BMC Bioinformatics
PMCID: 3212983
PMID: 21682902
DOI: 10.1186/1471-2105-12-245

[…] horter towards the C-terminus []. Overall, the six predictors under-predicted the disorder levels in this protein. They predicted only a few disordered residues at both termini, with the exception of Ucon that predicted about a dozen of short disordered segments throughout the entire chain and MFDp that predicted three disordered segments, including both termini and a segment between positions 421 […]

library_books

Predicting disordered regions in proteins using the profiles of amino acid indices

2009
BMC Bioinformatics
PMCID: 2648739
PMID: 19208144
DOI: 10.1186/1471-2105-10-S1-S42

[…] RONN [,], DisProt [,], NORSp [,], DISpro [], DISOPRED and DISOPRED2 [,], DisEMBL [], IUPred [], DRIP-PRED [] and Spritz [], and more recently DisPSSMP [], VSL1 and VSL2 [,], POODLE-L [], POODLE-S [], Ucon [], PrDOS [] and metaPrDOS []. Most existing predictors are based on the Neural Network and Support Vector Machine learning models. The features used to construct the prediction models include am […]

library_books

Large scale prediction of long disordered regions in proteins using random forests

2009
BMC Bioinformatics
PMCID: 2637845
PMID: 19128505
DOI: 10.1186/1471-2105-10-8

[…] D and DISOPRED2 [-], GlobPlot [] and DisEMBL [], IUPred [], Prelink [], DRIP-PRED (MacCallum, online publication ), FoldUnfold [], Spritz [], DisPSSMP [], VSL1 and VSL2 [,], POODLE-L [], POODLE-S [], Ucon [], PrDOS and metaPrDOS [,]. Among these predictors, neural networks and support vector machines (SVM) are widely used machine learning models.The accuracy of disorder predictors is generally lim […]

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UCON institution(s)
Department of Biochemistry and Molecular Biophysics, Columbia University, New-York, NY, USA; Columbia University Center for Computational Biology and Bioinformatics (C2B2), NorthEast Structural Genomics Consortium (NESG), New York, NY, USA
UCON funding source(s)
Supported by grants from the National Library of Medicine (NLM, RO1-LM07329), by a grant from the Protein Structure Initiative of the US National Institutes of Health to the Northeast Structural Genomics Consortium (U54-GM074958) and by the grant U54-GM072980 from the NIH.

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