Author

Lucia Montorsi

King's College LondonORCID 0000-0002-8791-5603Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:experimental assay· 1 Assay:imaging· 1 Research Focus:software / tool· 1 Research Focus:spatial domain detection· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Francesca D. CiccarelliiD· 2 shared Jo SpenceriD· 2 shared Michele BortolomeazziiD· 2 shared Amelia Acha‐SagredoiD· 1 shared Christopher YauiD· 1 shared Damjan TemelkovskiiD· 1 shared Gianluca BassoiD· 1 shared Kaspar MärtensiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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2 shared papersBioinformatics

Francesca D. CiccarelliORCID

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2 papers

Recent·Most cited

Rarity: Discovering rare cell populations from single-cell imaging data

Kaspar Märtens, Michele Bortolomeazzi, Lucia Montorsi, Jo Spencer, Francesca D. Ciccarelli, Christopher Yau

Rarity improves the detection of rare cell populations in single-cell imaging data through a Bayesian latent variable model.

Bioinformatics · Dec 1, 2023Peer-reviewedBioinformatics

A SIMPLI (Single-cell Identification from MultiPLexed Images) approach for spatially resolved tissue phenotypingat single-cell resolution.

Michele Bortolomeazzi, Lucia Montorsi, Damjan Temelkovski, Mohamed Reda Keddar, Amelia Acha‐Sagredo, Michael J. Pitcher, Gianluca Basso, Luigi Laghi, Manuel Rodriguez‐Justo, Jo Spencer, Francesca D. Ciccarelli

SIMPLI is a software tool for analyzing multiplexed imaging data to enable spatially resolved single-cell tissue phenotyping and marker expression quantification.

Nature Communications · Feb 9, 2022Peer-reviewedBioinformatics