PFRES statistics

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Citations per year

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Popular tool citations

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Associated diseases

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PFRES specifications


Unique identifier OMICS_19306
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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  • person_outline Lukasz Kurgan <>

Publication for PFRES

PFRES in publications

PMCID: 4127253
PMID: 25136571
DOI: 10.1155/2014/262850

[…] to identify folding types by introducing pseudo amino acid with sequential order information as a feature parameter and achieved an overall accuracy of 62.1%. chen and kurgan [] proposed the pfres method using evolutionary information and predicted secondary structure, obtaining an accuracy of 68.4%. ghanty and pal [] proposed the fusion of heterogeneous classifiers approach, […]

PMCID: 3577917
PMID: 23437146
DOI: 10.1371/journal.pone.0056499

[…] shen and chou later established an ensemble predictor called pfp-pred, based on protein fold prediction, to achieve 62.1% accuracy with the same dataset. another novel classifying method, pfres, proposed by chen and kurgan , used a smaller number of more effective features and attained an accuracy of 68.4%. the pfp-fundseqe predictor was subsequently used with chained functional […]

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PFRES institution(s)
Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
PFRES funding source(s)
Supported by the Alberta Ingenuity Scholarship and NSERC Canada.

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