Title |
Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics
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Published in |
BMC Bioinformatics, July 2011
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DOI | 10.1186/1471-2105-12-303 |
Pubmed ID | |
Authors |
Leonid L Chepelev, Alexandre Riazanov, Alexandre Kouznetsov, Hong Sang Low, Michel Dumontier, Christopher JO Baker |
Abstract |
The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 5% |
Japan | 1 | 3% |
Unknown | 34 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 16 | 43% |
Student > Ph. D. Student | 5 | 14% |
Professor > Associate Professor | 4 | 11% |
Student > Bachelor | 3 | 8% |
Other | 2 | 5% |
Other | 6 | 16% |
Unknown | 1 | 3% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 10 | 27% |
Agricultural and Biological Sciences | 8 | 22% |
Computer Science | 7 | 19% |
Biochemistry, Genetics and Molecular Biology | 3 | 8% |
Linguistics | 2 | 5% |
Other | 3 | 8% |
Unknown | 4 | 11% |