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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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Detalhes bibliográficos
Main Authors: Kangas, Lars J., Metz, Thomas O., Isaac, Giorgis, Schrom, Brian T., Ginovska-Pangovska, Bojana, Wang, Luning, Tan, Li, Lewis, Robert R., Miller, John H.
Formato: Artigo
Idioma:Inglês
Publicado em: Oxford University Press 2012
Assuntos:
Acesso em linha: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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