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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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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 in pipeline

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

[…] by removing similar sequence with fewer disordered residues. among the remaining 514 chains we removed four for which md failed to produce predictions; this also resulted in lack of predictions from ucon, profbval and norsnet that are bundled with the md predictions. moreover, we improved the annotations of the disprot chains using the procedure described in []. we applied the approach based […]


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UCON in publications

 (4)
library_books

MFDp2

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

[…] 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, […]

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

[…] predictors can be divided into 4 categories: i) methods that utilize the relative propensity of amino acids to form disorder/ordered regions which include globplot [], iupred [], foldindex [], and ucon []; ii) methods that are based on classifiers generated with the help of machine learning algorithms, such as dispro [], disopred [], disopred2 [], prdos [], poodle predictors [,], pondr […]

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

[…] [,], 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 […]

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

[…] 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 […]


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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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