Author

Marco Mondelli

Institute of Science and Technology AustriaORCID 0000-0002-3242-7020Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:variant effect prediction· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1 Research Focus:fine-mapping· 1

Frequent Co-Authors

Al DepopeiD· 2 shared Jakub BajzíkiD· 2 shared Matthew R. RobinsoniD· 2 shared Aleksej ZelezniakiD· 1 shared Alexander Sharipov· 1 shared Alexandra LesayováiD· 1 shared Anne RichmondiD· 1 shared Arturas GrauslysiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Al DepopeORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 14, 2026

Joint Variable Selection for Omic Biomarkers in Time-to-Event Data

Jakub Bajzík, Al Depope, Yasaman Zolfimoselo…·Matthew R. Robinson

The paper introduces vampW, a Bayesian method for joint variable selection in omic biomarkers and time-to-event data, showing reduced false discoveries and improved prediction.

DOI 10.64898/2026.04.30.721585

humanproteomics

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GeneticsbioRxivPreprintSep 14, 2023

Joint modelling of whole genome sequence data for human height via approximate message passing

Al Depope, Jakub Bajzík, Marco Mondelli, Matthew R. Robinson

This paper introduces gVAMP, an algorithm for analyzing whole genome sequence data to identify genetic variants associated with complex traits like height, showing improved accuracy over existing methods.

1 citation

humanwhole-genome sequencing

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