Author

Luciana Melina Luque

Harvard UniversityORCID 0000-0002-1010-3359Unclaimed 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:cell-cell communication· 2 Research Focus:differential expression· 2 Approach:graph neural network· 2 Organism:human· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Chris SanderiD· 2 shared Claudia Owczarek· 2 shared Giuseppe Torrisi· 2 shared Linus J. SchumacheriD· 2 shared Maddy ParsonsiD· 2 shared Asif KhaniD· 1 shared Assaf ZaritskyiD· 1 shared David T A HardmaniD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersCell Biology

Chris SanderORCID

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2 papers

Recent·Most cited

Data-modeling the interplay between single cell shape, single cell protein expression, and tissue state

Yuval Tamir, Yuval Bussi, Claudia Owczarek, Luciana Melina Luque, Giuseppe Torrisi, Leor Ariel Rose, Orit Kliper-Gross, Chris Sander, Linus J. Schumacher, Maddy Parsons, Leeat Keren, Assaf Zaritsky

The paper investigates the relationship between cell shape, protein expression, and tissue state using spatial imaging and machine learning, finding a bidirectional link and identifying p53-positive tumor cells.

Cell Reports Methods · May 15, 2026Peer-reviewedCell Biology

Identifying tissue states by spatial protein patterns related to chemotherapy response in triple-negative breast cancer

Luciana Melina Luque, Asif Khan, Giuseppe Torrisi, Tessa D Green, David T A Hardman, Claudia Owczarek, T. A. Phillips, Debora S. Marks, Maddy Parsons, Chris Sander, Linus J. Schumacher

This study develops a computational pipeline for analyzing spatial proteomics data to identify tissue states associated with chemotherapy response in TNBC, revealing distinct spatial patterns and predictive markers.

bioRxiv · Oct 6, 2025 · PreprintCancer Biology