Author

Mohammed Charrout

Delft University of TechnologyORCID 0000-0002-3405-1995Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Immunology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Assay:flow cytometry· 1

Frequent Co-Authors

Ahmed Essam MahfouziD· 3 shared Marcel J. T. ReindersiD· 2 shared Dicky L. TahaparyiD· 1 shared Ibrahima Diallo· 1 shared Jeremia Jackson PyuzaiD· 1 shared Koen A. StamiD· 1 shared Maria YazdanbakhshiD· 1 shared Marion König· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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3 shared papersBioinformatics

Ahmed Essam MahfouzORCID

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Author profile →

3 papers

Recent·Most cited

Mass cytometry data integration methods reveal rural-urban gradient of immune profiles across geography

Koen A. Stam, Jeremia Jackson Pyuza, Mikhael D. Manurung, Dicky L. Tahapary, Taniawati Supali, Marloes M.A.R. van Dorst, Ahmed Essam Mahfouz, Mohammed Charrout, Simon P. Jochems, Wesley Huisman, Marion König, Yvonne C.M. Kruize, Marouba Cisse, Ibrahima Diallo, Moustapha Mbow, , Wouter A. A. de Steenhuijsen Piters

This study integrates mass cytometry data from diverse populations to identify immune signatures associated with rural living, finding shared differences in lymphocyte and innate immune cell characteristics.

bioRxiv · Sep 5, 2025 · PreprintImmunology

Benchmarking Variational AutoEncoders on cancer transcriptomics data

Mostafa Eltager, Tamim Abdelaal, Mohammed Charrout, Ahmed Essam Mahfouz, Marcel J. T. Reinders, Stavros Makrodimitris

This study benchmarks variational autoencoders on cancer transcriptomics data to evaluate hyperparameter effects and latent space biological relevance.

PLoS ONE · Oct 5, 2023Peer-reviewedBioinformatics

Untangling biological factors influencing trajectory inference from single cell data

Mohammed Charrout, Marcel J. T. Reinders, Ahmed Essam Mahfouz

The paper identifies and removes confounding biological factors like the cell cycle from single-cell data to improve trajectory inference accuracy.

NAR Genomics and Bioinformatics · Jul 22, 2020Peer-reviewedBioinformatics