Author

Morgane Wartel

European Molecular Biology LaboratoryORCID 0000-0002-4955-7972Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Microbiology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:E. coli· 2 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Assay:proteomics· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Alexandra KoumoutsiiD· 1 shared Ana Rita BrochadoiD· 1 shared André MateusiD· 1 shared Anja TelzerowiD· 1 shared Athanasios TypasiD· 1 shared Christian L. MülleriD· 1 shared Christoph Binsfeld· 1 shared Érick DenamuriD· 1 shared

Activity by Year

2017-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 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

1 shared paperSystems Biology

Alexandra KoumoutsiORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Systematic Characterization of Transport Regulation in Escherichia coli across defined environmental cues

Christoph Binsfeld, Roberto Olayo-Alarcón, Lucía Pérez Jiménez, Morgane Wartel, Mara Stadler, André Mateus, Christian L. Müller, Ana Rita Brochado

The paper systematically characterizes transport regulation in E. coli across 94 chemical cues, revealing new transcriptional responses and the role of regulators like Rob.

PLoS Biology · Jul 22, 2025Peer-reviewedMicrobiology

Phenotype prediction in an Escherichia coli strain panel

Marco Galardini, Alexandra Koumoutsi, Lucía Herrera-Domínguez, Juan Antonio Cordero Varela, Anja Telzerow, Omar Wagih, Morgane Wartel, Olivier Clermont, Érick Denamur, Athanasios Typas, Pedro Beltrão

The paper predicts growth defects in Escherichia coli strains using genetic variant impact models and gene function data, achieving reliable predictions for up to 38% of tested conditions.

eLife · Dec 27, 2017Peer-reviewedSystems Biology