Author

Bruno Le Bizec

Institut National de Recherche pour l'Agriculture, l'Alimentation et l'EnvironnementORCID 0000-0002-0600-5895Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:machine learning (classical)· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Organism:human· 1 Assay:metabolomics· 1 Assay:metagenomics· 1

Frequent Co-Authors

Yann GuittoniD· 2 shared Aaron FaitiD· 1 shared Adolfo AmézquitaiD· 1 shared Aleksandr Alekseevich SmirnoviD· 1 shared Alexander A. AksenoviD· 1 shared Alexey V. MelnikiD· 1 shared Alisdair Robert FernieiD· 1 shared Amina BouslimaniiD· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Yann GuittonORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS.

Alexander A. Aksenov, Ivan Laponogov, Zheng Zhang, Sophie L. F. Doran, Ilaria Belluomo, Dennis A. Veselkov, Wout Bittremieux, Louis-Félix Nothias-Scaglia, Mélissa Nothias-Esposito, Katherine N. Maloney, Biswapriya B. Misra, Alexey V. Melnik, Aleksandr Alekseevich Smirnov, Xiuxia Du, Kenneth Lyons Jones, , Kirill Veselkov

The paper develops a machine learning workflow for auto-deconvolution of GC-MS data within GNPS, enabling molecular networking and applications in breathomics and volatilome mapping.

Nature Biotechnology · Nov 9, 2020Peer-reviewedBioinformatics

WiPP: Workflow for improved Peak Picking for Gas Chromatography-Mass Spectrometry (GC-MS) data

Nico Borgsmüller, Yoann Gloaguen, Tobias Opialla, Eric Blanc, Emilie Sicard, Anne‐Lise Royer, Bruno Le Bizec, Stéphanie Durand, Carole Migné, Mélanie Pétéra, Estelle Pujos‐Guillot, Franck Giacomoni, Yann Guitton, Dieter Beule, Jennifer Kirwan

WiPP improves GC-MS peak detection by combining multi-algorithm results with machine learning-based quality assessment, enhancing accuracy and enabling algorithm comparison.

Metabolites · Aug 21, 2019Peer-reviewedBioinformatics