Artículo
Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data
Aksenov, Alexander A.; Laponogov, Ivan; Zhang, Zheng; Doran, Sophie L. F.; Belluomo, Ilaria; Veselkov, Dennis; Bittremieux, Wout; Nothias, Louis Felix; Nothias Esposito, Mélissa; Maloney, Katherine N.; Misra, Biswapriya B.; Melnik, Alexey V.; Smirnov, Aleksandr; Du, Xiuxia; Jones, Kenneth L.; Dorrestein, Kathleen; Panitchpakdi, Morgan; Ernst, Madeleine; van der Hooft, Justin J. J.; Gonzalez, Mabel; Carazzone, Chiara; Amézquita, Adolfo; Callewaert, Chris; Morton, James T.; Quinn, Robert A.; Bouslimani, Amina; Albarracín Orio, Andrea Georgina
; Petras, Daniel; Smania, Andrea
; Couvillion, Sneha P.; Burnet, Meagan C.; Nicora, Carrie D.; Zink, Erika; Metz, Thomas O.; Artaev, Viatcheslav; Humston Fulmer, Elizabeth; Gregor, Rachel; Meijler, Michael M.; Mizrahi, Itzhak; Eyal, Stav; Anderson, Brooke; Dutton, Rachel; Lugan, Raphaël; Boulch, Pauline Le; Guitton, Yann; Prevost, Stephanie; Poirier, Audrey; Dervilly, Gaud; Le Bizec, Bruno; Fait, Aaron; Persi, Noga Sikron; Song, Chao; Gashu, Kelem; Coras, Roxana; Guma, Monica; Manasson, Julia; Scher, Jose U.; Barupal, Dinesh Kumar; Alseekh, Saleh; Fernie, Alisdair R.; Mirnezami, Reza; Vasiliou, Vasilis; Schmid, Robin; Borisov, Roman S.; Kulikova, Larisa N.; Knight, Rob; Wang, Mingxun; Hanna, George B.; Dorrestein, Pieter; Veselkov, Kirill
; Petras, Daniel; Smania, Andrea
; Couvillion, Sneha P.; Burnet, Meagan C.; Nicora, Carrie D.; Zink, Erika; Metz, Thomas O.; Artaev, Viatcheslav; Humston Fulmer, Elizabeth; Gregor, Rachel; Meijler, Michael M.; Mizrahi, Itzhak; Eyal, Stav; Anderson, Brooke; Dutton, Rachel; Lugan, Raphaël; Boulch, Pauline Le; Guitton, Yann; Prevost, Stephanie; Poirier, Audrey; Dervilly, Gaud; Le Bizec, Bruno; Fait, Aaron; Persi, Noga Sikron; Song, Chao; Gashu, Kelem; Coras, Roxana; Guma, Monica; Manasson, Julia; Scher, Jose U.; Barupal, Dinesh Kumar; Alseekh, Saleh; Fernie, Alisdair R.; Mirnezami, Reza; Vasiliou, Vasilis; Schmid, Robin; Borisov, Roman S.; Kulikova, Larisa N.; Knight, Rob; Wang, Mingxun; Hanna, George B.; Dorrestein, Pieter; Veselkov, Kirill
Fecha de publicación:
09/02/2021
Editorial:
Nature Publishing Group
Revista:
Nature Biotechnology
ISSN:
1087-0156
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography–mass spectrometry (GC–MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC–MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.
Palabras clave:
METABOLOMICS
,
GC-MS
,
MACHINE LEARNING
,
NATURAL PRODUCTS
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2.971Mb
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Licencia
Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción:
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
Colecciones
Articulos(IRNASUS)
Articulos de INSTITUTO DE INVESTIGACIONES EN RECURSOS NATURALES Y SUSTENTABILIDAD JOSE SANCHEZ LABRADOR S.J.
Articulos de INSTITUTO DE INVESTIGACIONES EN RECURSOS NATURALES Y SUSTENTABILIDAD JOSE SANCHEZ LABRADOR S.J.
Citación
Aksenov, Alexander A.; Laponogov, Ivan; Zhang, Zheng; Doran, Sophie L. F.; Belluomo, Ilaria; et al.; Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data; Nature Publishing Group; Nature Biotechnology; 39; 2; 9-2-2021; 169-173
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