Author

Francesco Casalegno

École Polytechnique Fédérale de LausanneORCID 0000-0001-7230-2292Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Neuroscience· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:cell type annotation· 1 Approach:deep learning· 1 Approach:graph neural network· 1

Frequent Co-Authors

Émilie DelattreiD· 1 shared Felix SchürmanniD· 1 shared Henry MarkramiD· 1 shared Jelena Banjac Lukic· 1 shared Julie MeystreiD· 1 shared Lida KanariiD· 1 shared Michaël DefferrardiD· 1 shared Stanislav SchmidtiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperNeuroscience

Émilie DelattreORCID

Mutual co-authors in cluster

Author profile →

1 paper

Recent·Most cited

An interpretable deep learning framework for classifying neuronal morphologies using topology and graph neural networks

Lida Kanari, Stanislav Schmidt, Francesco Casalegno, Émilie Delattre, Jelena Banjac Lukic, Thomas Negrello, Ying Shi, Julie Meystre, Michaël Defferrard, Felix Schürmann, Henry Markram

This paper presents a deep learning framework that classifies neuronal morphologies using topology and graph neural networks, achieving accuracy comparable to human experts.

Scientific Reports · Sep 22, 2026Peer-reviewedNeuroscience