Author

Mahdi Safarpour

University of AntwerpORCID 0000-0002-5736-4433Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Anna Rosanas‐UrgelliD· 1 shared Annelies Van RieiD· 1 shared Christopher Delgado-RattoiD· 1 shared Dionicia GamboaiD· 1 shared Emmanuel RivièreiD· 1 shared Johanna Helena KattenbergiD· 1 shared Joseph Michael VinetziD· 1 shared Luis Cabrera-SosaiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperGenomics

Anna Rosanas‐UrgellORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintFeb 14, 2026

Feature-based in-silico model to predict the Mycobacterium tuberculosis bedaquiline phenotype associated with Rv0678 variants

Wilma Ursula Quispe-Rojas, M. Fuertes, Vincent Rennie…·Annelies Van Rie

The paper develops a machine learning model to predict bedaquiline resistance in Mycobacterium tuberculosis based on Rv0678 variants, achieving high accuracy in internal validation.

DOI 10.64898/2026.02.12.705543

machine learning (classical)variant effect prediction

𝕏 PostBluesky

GenomicsFrontiers in GeneticsPeer-reviewedDec 19, 2024

Comparing newly developed SNP barcode panels with microsatellites to explore population genetics of malaria parasites in the Peruvian Amazon

Luis Cabrera-Sosa, Mahdi Safarpour, Johanna Helena Kattenberg…·Christopher Delgado-Ratto

The paper compares SNP barcode panels with microsatellites to assess population genetics of malaria parasites in the Peruvian Amazon, finding comparable results between the methods.

2 citations

statistical modelbenchmarking

𝕏 PostBluesky