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In silico identification software (ISIS): a machine learning approach to tandem mass spectral identification of lipids
Motivation: Liquid chromatography–mass spectrometry-based metabolomics has gained importance in the life sciences, yet it is not supported by software tools for high throughput identification of metabolites based on their fragmentation spectra. An algorithm (ISIS: in silico identification software)...
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| Hauptverfasser: | , , , , , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Oxford University Press
2012
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3381961/ https://ncbi.nlm.nih.gov/pubmed/22592377 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/bts194 |
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