Author

Lorenzo Dall’Olio

Istituto delle Scienze Neurologiche di BolognaORCID 0000-0002-8907-0034Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Immunology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:cell type annotation· 2 Organism:human· 2 Assay:proteomics· 2 Research Focus:spatial domain detection· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Gastone CastellaniiD· 2 shared Giorgio CattorettiiD· 2 shared Maddalena M. BolognesiiD· 2 shared Simone BorghesiiD· 2 shared Amy MaerteniD· 1 shared Ann M. HabermaniD· 1 shared Francesca Maria BosisioiD· 1 shared Giulio Eugenio MandelliiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 40 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

2 shared papersImmunology

Gastone CastellaniORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

The normal human lymph node cell classification and landscape defined by high-dimensional spatial proteomics.

Maddalena M. Bolognesi, Lorenzo Dall’Olio, Giulio Eugenio Mandelli, Luisa Lorenzi, Francesca Maria Bosisio, Ann M. Haberman, Govind Bhagat, Simone Borghesi, Mario Faretta, Gastone Castellani, Giorgio Cattoretti

This study classifies and maps cell types in normal human lymph nodes using high-dimensional spatial proteomics, revealing novel cell subsets and interactions.

PLoS ONE · Apr 21, 2026Peer-reviewedImmunology

Seeing or believing in hyperplexed spatial proteomics via antibodies. New and old biases for an image-based technology.

Maddalena M. Bolognesi, Lorenzo Dall’Olio, Amy Maerten, Simone Borghesi, Gastone Castellani, Giorgio Cattoretti

The paper evaluates biases in hyperplexed spatial proteomics, showing human eye limitations and demonstrating the value of computational tools like BRAQUE for analyzing low-signal data.

Biological Imaging · Jan 1, 2024Peer-reviewedSystems Biology