Author

Michele Chirichella

AstraZeneca (United Kingdom)ORCID 0000-0003-1961-3758Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Organism:mouse· 1

Frequent Co-Authors

Antonino CattaneoiD· 1 shared Darren J. SchofieldiD· 1 shared Davide AngelettiiD· 1 shared Federico CremisiiD· 1 shared Ivan ArisiiD· 1 shared Luca PandolfiniiD· 1 shared Marco FantiniiD· 1 shared Marco TerrignoiD· 1 shared

Activity by Year

2017-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

Antonino CattaneoORCID

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2 papers

Recent·Most cited

ImmunologyCell SystemsPeer-reviewedFeb 1, 2026

Integrated single-cell analyses of affinity-tested B-cells enable the identification of a gene signature to predict antibody affinity.

Michele Chirichella, Matthew Ratcliff, Shuang Gu…·Darren J. Schofield

The paper identifies a transcriptomic signature, 'High Signature', that predicts high-affinity antibodies from B-cells without sequence analysis.

2 citationstop 4%

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BioinformaticsPLoS ONEPeer-reviewedMay 15, 2017

Assessment of Antibody Library Diversity through Next Generation Sequencing and Technical Error Compensation.

Marco Fantini, Luca Pandolfini, Simonetta Lisi…·Antonino Cattaneo

This paper introduces a PCR-free NGS approach and software (DEAL) to accurately estimate antibody library diversity by accounting for sequencing errors.

25 citations

statistical modelbenchmarking

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