Open Access Highly Accessed Research article

Self-organizing ontology of biochemically relevant small molecules

Leonid L Chepelev1*, Janna Hastings2, Marcus Ennis2, Christoph Steinbeck2 and Michel Dumontier134

Author Affiliations

1 Department of Biology, Carleton University, Ottawa, Canada

2 European Bioinformatics Institute, Wellcome Trust Genome Centre, Hinxton, UK

3 School of Computer Science, Carleton University, Ottawa, Canada

4 Institute of Biochemistry, Carleton University, Ottawa, Canada

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BMC Bioinformatics 2012, 13:3  doi:10.1186/1471-2105-13-3

Published: 6 January 2012

Additional files

Additional file 1:

Detailed analysis of results of automated chemical annotation by human curators. This file contains the results of automated chemical entity classification as well as the assessment of these classifications by a human curator as correct and direct (inferred classification is identical to training set classification). Comments on decisions to view a particular classification as erroneous or correct are also included.

Format: XLS Size: 75KB Download file

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Additional file 2:

Chemical entities to train and assess definitions for each class. This file contains the complete collection of chemical entities collected by human curators to compute chemical class definitions as described (see Methods). The names for each class as used in this work are also reported, along with the class ID for the ChEBI classes.

Format: XLS Size: 108KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data