Evidence map›Paper›PMID 27867422›Full record

ArticleJournal of cheminformatics2016

ClassyFire: automated chemical classification with a comprehensive, computable taxonomy.

Yannick Djoumbou Feunang, Roman Eisner, Craig Knox, Leonid Chepelev, Janna Hastings, Gareth Owen, Eoin Fahy, Christoph Steinbeck, Shankar Subramanian, Evan Bolton and 2 more

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 731 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
731citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

731 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. ManagingMolecules (Basel, Switzerland) · 2025
    Pooled it
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  5. Integrative physiological and metabolomic study of Hirschfeldia incana under short- and medium-term lead (Pb) stress.Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine · 2026
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671 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Yannick Djoumbou FeunangDepartment of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8 Canada.
Roman EisnerJobber - Field Service Software, 10520 Jasper Ave, Edmonton, AB T5J 1Z7 Canada.
Craig KnoxDepartment of Computing Science, University of Alberta, Edmonton, AB T6G 2E8 Canada.
Leonid ChepelevDepartment of Medical Imaging, The Ottawa Hospital, University of Ottawa, Civic Campus, 1053 Carling Ave, Ottawa, ON K1Y 4E9 Canada.
Janna HastingsEuropean Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge UK.
Gareth OwenEuropean Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge UK.
Eoin FahyDepartment of Bioengineering, University of California, La Jolla, San Diego, CA 92093 USA.
Christoph SteinbeckEuropean Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge UK.
Shankar SubramanianDepartment of Bioengineering, University of California, La Jolla, San Diego, CA 92093 USA.
Evan BoltonDepartment of Health and Human Services, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894 USA.
Russell GreinerDepartment of Computing Science, University of Alberta, Edmonton, AB T6G 2E8 Canada ; Department of Computing Science 2-21 Athabasca Hall, Alberta Innovates Centre for Machine Learning (AICML), University of Alberta, Edmonton, AB T6G 2E8 Canada.
David S WishartDepartment of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8 Canada ; Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8 Canada ; National Research Council, National Institute for Nanotechnology (NINT), Edmonton, AB T6G 2M9 Canada ; The Metabolomics Innovation Center, University of Alberta, Edmonton, AB T6G 2E9 Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundScientists have long been driven by the desire to describe, organize, classify, and compare objects using taxonomies and/or ontologies. In contrast to biology, geology, and many other scientific disciplines, the world of chemistry still lacks a standardized chemical ontology or taxonomy. Several attempts at chemical classification have been made; but they have mostly been limited to either manual, or semi-automated proof-of-principle applications. This is regrettable as comprehensive chemical classification and description tools could not only improve our understanding of chemistry but also improve the linkage between chemistry and many other fields. For instance, the chemical classification of a compound could help predict its metabolic fate in humans, its druggability or potential hazards associated with it, among others. However, the sheer number (tens of millions of compounds) and complexity of chemical structures is such that any manual classification effort would prove to be near impossible.

resultsWe have developed a comprehensive, flexible, and computable, purely structure-based chemical taxonomy (ChemOnt), along with a computer program (ClassyFire) that uses only chemical structures and structural features to automatically assign all known chemical compounds to a taxonomy consisting of >4800 different categories. This new chemical taxonomy consists of up to 11 different levels (Kingdom, SuperClass, Class, SubClass, etc.) with each of the categories defined by unambiguous, computable structural rules. Furthermore each category is named using a consensus-based nomenclature and described (in English) based on the characteristic common structural properties of the compounds it contains. The ClassyFire webserver is freely accessible at http://classyfire.wishartlab.com/. Moreover, a Ruby API version is available at https://bitbucket.org/wishartlab/classyfire_api, which provides programmatic access to the ClassyFire server and database. ClassyFire has been used to annotate over 77 million compounds and has already been integrated into other software packages to automatically generate textual descriptions for, and/or infer biological properties of over 100,000 compounds. Additional examples and applications are provided in this paper.

conclusionClassyFire, in combination with ChemOnt (ClassyFire's comprehensive chemical taxonomy), now allows chemists and cheminformaticians to perform large-scale, rapid and automated chemical classification. Moreover, a freely accessible API allows easy access to more than 77 million "ClassyFire" classified compounds. The results can be used to help annotate well studied, as well as lesser-known compounds. In addition, these chemical classifications can be used as input for data integration, and many other cheminformatics-related tasks.

Indexed as

AnnotationDatabaseData integrationInferenceOntologyStructure-based classificationTaxonomyText-based search

Identifiers

PMID27867422
PMCPMC5096306

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.