Author

Atte Aalto

University of LuxembourgORCID 0000-0002-6876-474XUnclaimed 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 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:multiome· 1 Approach:optimal transport· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Jorge M. GonçalvesiD· 2 shared Aakansha RaiiD· 1 shared Ádám Misák· 1 shared Akash Gosain· 1 shared Alexander Wu· 1 shared Alice DriesseniD· 1 shared Alidivinas Prusokas· 1 shared Anand Rajasekar· 1 shared

Activity by Year

2021-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Jorge M. GonçalvesORCID

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2 papers

Recent·Most cited

Gene regulatory network inference from single-cell data using optimal transport

François Lamoline, Isabel Haasler, Johan Karlsson, Jorge M. Gonçalves, Atte Aalto

This paper introduces GRIT, a method for inferring gene regulatory networks from single-cell data using optimal transport to model the evolution of cell distributions over time.

Bioinformatics · Jul 12, 2025Peer-reviewedBioinformatics

Cell-to-cell and type-to-type heterogeneity of signaling networks: Insights from the crowd

Attila Gábor, Marco Tognetti, Alice Driessen, Jovan Tanevski, Baosen Guo, Wencai Cao, He Shen, Thomas Von Yu, Verena Chung, Bernd Bodenmiller, Julio Sáez-Rodríguez, Augustinas Prusokas, Alidivinas Prusokas, Renata Retkutė, Anand Rajasekar, , Mingyu Lee

The paper organizes a DREAM challenge to benchmark predictive models of single-cell signaling using mass cytometry data from breast cancer cell lines.

Molecular Systems Biology · Oct 1, 2021Peer-reviewedBioinformatics