Author

Lisa Gennai

École Polytechnique Fédérale de LausanneORCID 0009-0000-6156-5804Unclaimed 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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Assay:protein sequence· 2 Approach:statistical model· 2 Organism:bacteria (other)· 1 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

Andrea PagnaniiD· 2 shared Francesco CareddaiD· 2 shared Paolo De Los RiosiD· 2 shared Mathieu Edouard RebeaudiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersBioinformatics

Andrea PagnaniORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 8, 2026

Partner determination from protein sequences using class information

Lisa Gennai, F. Caredda, Mathieu Edouard Rebeaud…·Paolo De Los Rios

The paper introduces CLAPP, a method to determine paralog interactions by class, showing it can accurately assign interaction partners using weak or noisy scores when class labels are reliable.

DOI 10.64898/2026.05.06.723283

bacteria (other)protein sequence

𝕏 PostBluesky

BioinformaticsPLoS Computational BiologyPeer-reviewedFeb 19, 2026

Controllable Protein Design via Autoregressive Direct Coupling Analysis Conditioned on Principal Components

Francesco Caredda, Lisa Gennai, Paolo De Los Rios, Andrea Pagnani

FeatureDCA improves protein sequence generation by conditioning DCA on principal components, achieving accurate structural and functional results across multiple families.

1 citation

protein sequencestatistical model

𝕏 PostBluesky