ClassyFire statistics

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Citations per year

Number of citations per year for the bioinformatics software tool ClassyFire

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ClassyFire specifications


Unique identifier OMICS_24908
Name ClassyFire
Interface Web user interface
Restrictions to use None
Output data Standard chemical classification data, a list of chemical substituents, and a secondary attribute called the “Molecular Framework” (for many compounds).
Output format HTML+(JSON,SDF,CSV)
Computer skills Basic
Version 1.0
Stability Stable
Maintained Yes

Additional information

Publication for ClassyFire

ClassyFire citations


IMPPAT: A curated database of Indian Medicinal Plants, Phytochemistry And Therapeutics

Sci Rep
PMCID: 5847565
PMID: 29531263
DOI: 10.1038/s41598-018-22631-z

[…] our database (Supplementary Table ).Figure 3IMPPAT captures information on 27074 plant-phytochemical associations which encompasses 1742 Indian medicinal plants and their 9596 phytochemicals. We used ClassyFire webserver for chemical classification of the 9596 IMPPAT phytochemicals (Methods). The 9596 IMPPAT phytochemicals are distributed across 24 super-classes, 260 classes and 415 sub-classes of […]


A census of P. longum’s phytochemicals and their network pharmacological evaluation for identifying novel drug like molecules against various diseases, with a special focus on neurological disorders

PLoS One
PMCID: 5761900
PMID: 29320554
DOI: 10.1371/journal.pone.0191006

[…] An automated and rapid chemical classification method “ClassyFire” [] was used to assign a chemical class to the phytochemicals. The query is mapped to the various classes based on its features that are calculated using superstructure-search operations an […]


An algorithm to identify functional groups in organic molecules

J Cheminform
PMCID: 5462667
DOI: 10.1186/s13321-017-0225-z

[…] sify molecules into categories []. An example of this type of publications is work by Bobach et al. describing a rule-based definition of chemical classes to classify compounds into classes [] or the ClassyFire software [] developed in the Wishart’s group allowing chemists to perform large-scale automated chemical classification based on a structure-based chemical taxonomy consisting of over 4800 […]


Novel application of heuristic optimisation enables the creation and thorough evaluation of robust support vector machine ensembles for machine learning applications

PMCID: 4655007
PMID: 26617479
DOI: 10.1007/s11306-015-0894-4

[…] %, the values corresponding respectively to the upper 95 and 99 % confidence levels of the permuted distribution (Fig. c); the 95 % confidence interval of the distribution is retrieved using built-in classyfire functions as part of the “five number summary”, and can be graphically represented as in Figs. d and d. Similarly, in the case of the brain data, the non-permuted classification accuracy wa […]

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ClassyFire institution(s)
Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada; Jobber – Field Service Software, Edmonton, AB, Canada; Department of Computing Science, University of Alberta, Edmonton, AB, Canada; National Research Council, National Institute for Nanotechnology (NINT), Edmonton, AB, Canada; Department of Medical Imaging, The Ottawa Hospital, University of Ottawa, Civic Campus, Ottawa, ON, Canada; European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK; Department of Bioengineering, University of California, La Jolla, San Diego, CA, USA; Department of Health and Human Services, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA; Department of Computing Science, Alberta Innovates Centre for Machine Learning (AICML), University of Alberta, Edmonton, AB, Canada; The Metabolomics Innovation Center, University of Alberta, Edmonton, AB, Canada
ClassyFire funding source(s)
Supported by Genome Canada, Genome Alberta, The Canadian Institutes of Health Research, Alberta Innovates, The National Research Council and The National Institute of Nanotechnology.

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