Author

D. Moradigaravand

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Microbiology· 3

Signature Assays, Organisms & Methods

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Organism:E. coli· 3 Approach:experimental assay· 2 Assay:whole-genome sequencing· 2 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

A. Farewell· 2 shared J. Warringer· 2 shared L. Parts· 2 shared M. Palm· 2 shared V. Mustonen· 2 shared C. D. Neilson· 1 shared E. C. A. Goodall· 1 shared F. de Cogan· 1 shared

Activity by Year

2021-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersMicrobiology

A. Farewell

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Author profile →

3 papers

Recent·Most cited

Genome-wide synthetic-lethality screen of Bam complex associated genes in Escherichia coli

J. A. Bryant, K. A. Staunton, H. M. Doherty, M. B. Alao, X. Ma, J. Morcinek-Orlowska, E. C. A. Goodall, J. Gray, M. Milner, L. Kidger, C. D. Neilson, J. A. Cole, F. de Cogan, T. J. Knowles, M. K. Glinkowska, , M. Banzhaf

The paper identifies synthetic-lethal interactions of Bam complex associated genes in E. coli, revealing dependencies on lipid composition and peptidoglycan synthesis.

bioRxiv · Jul 5, 2023Microbiology

Machine-learning prediction of resistance to sub-inhibitory antimicrobial concentrations from Escherichia coli genomes

S. Benkwitz-Bedford, M. Palm, T. Y. Demirtas, V. Mustonen, A. Farewell, J. Warringer, D. Moradigaravand, L. Parts

This paper uses machine learning to predict E. coli growth under sub-inhibitory antimicrobial concentrations from genomic data, finding moderate to strong correlations but highlighting remaining missing heritability.

bioRxiv · Mar 26, 2021 · PreprintMicrobiology

Genomic epidemiology and evolution of Escherichia coli in wild animals

R. Murphy, M. Palm, V. Mustonen, J. Warringer, A. Farewell, D. Moradigaravand, L. Parts

This study analyzes whole genome sequencing data of commensal E. coli from wild animals to explore population structure, host associations, and the presence of virulence and antibiotic resistance genes.

mSphere · Feb 24, 2021Peer-reviewedMicrobiology