Author

Alex van Belkum

bioMérieux (France)ORCID 0000-0001-8545-5108Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genomics· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 2 Approach:experimental assay· 2 Approach:statistical model· 2 Assay:whole-genome sequencing· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Research Focus:fine-mapping· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Magali JaillardiD· 2 shared Aleksandre JaparidzeiD· 1 shared Cees DekkeriD· 1 shared Elliot WhittardiD· 1 shared Farbod AlijaniiD· 1 shared I. E. RosłońiD· 1 shared James RedferniD· 1 shared Janine Wallace· 1 shared

Activity by Year

2018-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersGenomics

Magali JaillardORCID

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3 papers

Recent·Most cited

MicrobiologyApplied Physics LettersPeer-reviewedJan 1, 2024

Prospects and Challenges for Graphene Drums As Sensors Of Individual Bacteria

I. E. Rosłoń, Aleksandre Japaridze, L.-V. Naarden…·Farbod Alijani

This paper discusses the potential of graphene drums as nanomotion sensors for studying microbial processes at the single-cell level and explores their future applications in clinical settings.

14 citations

bacteria (other)experimental assay

𝕏 PostBluesky

GenomicsBMC GenomicsPeer-reviewedJul 26, 2021

Biofilm Associated Genotypes of Multidrug-Resistant Pseudomonas aeruginosa

James Redfern, Janine Wallace, Alex van Belkum…·Mark C. Enright

This study uses genome-wide association methods to identify genetic factors associated with biofilm production in Pseudomonas aeruginosa isolates.

29 citations

humanwhole-genome sequencing

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BioinformaticsPLoS GeneticsPeer-reviewedNov 12, 2018

A fast and agnostic method for bacterial genome-wide association studies: bridging the gap between kmers and genetic events

Magali Jaillard, Leandro Lima, Maud Tournoud…·Laurent Jacob

DBGWAS is a fast, alignment-free method for bacterial GWAS that identifies interpretable genetic variants associated with phenotypes by analyzing kmer-based subgraphs.

222 citationstop 2%

bacteria (other)whole-genome sequencing

𝕏 PostBluesky