Title |
BiNChE: A web tool and library for chemical enrichment analysis based on the ChEBI ontology
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Published in |
BMC Bioinformatics, February 2015
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DOI | 10.1186/s12859-015-0486-3 |
Pubmed ID | |
Authors |
Pablo Moreno, Stephan Beisken, Bhavana Harsha, Venkatesh Muthukrishnan, Ilinca Tudose, Adriano Dekker, Stefanie Dornfeldt, Franziska Taruttis, Ivo Grosse, Janna Hastings, Steffen Neumann, Christoph Steinbeck |
Abstract |
Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis. We describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology. BiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Japan | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Switzerland | 1 | 2% |
South Africa | 1 | 2% |
Brazil | 1 | 2% |
Unknown | 46 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 20 | 41% |
Student > Ph. D. Student | 10 | 20% |
Student > Master | 5 | 10% |
Student > Postgraduate | 3 | 6% |
Student > Bachelor | 2 | 4% |
Other | 3 | 6% |
Unknown | 6 | 12% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 19 | 39% |
Biochemistry, Genetics and Molecular Biology | 8 | 16% |
Computer Science | 6 | 12% |
Chemistry | 2 | 4% |
Medicine and Dentistry | 2 | 4% |
Other | 5 | 10% |
Unknown | 7 | 14% |