Author

Kevin de Azevedo

Goethe University FrankfurtORCID 0000-0003-4714-9526Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Organism:human· 2 Approach:Bayesian inference· 1 Research Focus:cell type annotation· 1 Research Focus:dimensionality reduction· 1 Research Focus:gene regulatory network inference· 1 Assay:multiome· 1 Assay:scRNA-seq· 1 Approach:statistical model· 1

Frequent Co-Authors

Florian BuettneriD· 2 shared Sareh AmeriFar· 1 shared Zahra Moslehi· 1 shared

Activity by Year

2024-2025 · peak 1/yr

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3 top collaborators · 3 mutual co-author links

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2 shared papersBioinformatics

Florian BuettnerORCID

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2 papers

Recent·Most cited

BioinformaticsNucleic Acids ResearchPeer-reviewedJul 19, 2025

Learning interpretable representations of single-cell multi-omics data with multi-output Gaussian Processes

Zahra Moslehi, Sareh AmeriFar, Kevin de Azevedo, Florian Buettner

This paper introduces a model that combines expressive representation learning with interpretable Gaussian processes to analyze single-cell multi-omics data, revealing relationships between cell clusters and marker genes.

DOI 10.1093/nar/gkaf630

humanscRNA-seq

𝕏 PostBluesky

BioinformaticsbioRxivPreprintNov 4, 2024

Unified Analysis of Multi-order Tensors for Integrative Molecular Profiling

Kevin de Azevedo, Florian Buettner

The paper introduces MUSIC, a Bayesian tensor decomposition framework for integrating multi-modal molecular data, showing it reveals interpretable patterns across patients, cell types, and modalities.

DOI 10.1101/2024.11.04.621951

humanmultiome

𝕏 PostBluesky