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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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| Autores principales: | , , , , , , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Oxford University Press
2012
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| Materias: | |
| Acceso en línea: | 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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