Author

Yardena Samuels

Weizmann Institute of ScienceORCID 0000-0002-3349-7266Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Organism:mouse· 1 Approach:optimal transport· 1

Frequent Co-Authors

Alejandro A. SchäfferiD· 1 shared Andrew Craig· 1 shared Avital Sarusi-PortugueziD· 1 shared Aviya Habshush MenachemiD· 1 shared Barak Toval· 1 shared Charles SwantoniD· 1 shared Charlotte Boulton· 1 shared Chen WelleriD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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1 shared paperBioinformatics

Alejandro A. SchäfferORCID

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3 papers

Recent·Most cited

Epithelial MHC II antigen presentation dynamically informs intestinal homeostasis and injury

V. V. Holiar, Vladislav Rudenko, Chen Weller, Mariia Naumova, Sacha Lebon, Marco Canella, Petro Busko, Avital Sarusi-Portuguez, Tali Shalit, Aviya Habshush Menachem, Idan Adir, Zachary Petrover, Polina Greenberg, Corine Katina, Polina Gradchenko, , Moshe Biton

This study shows that epithelial MHC II antigen presentation encodes tissue state and injury signals, maintaining homeostasis and promoting tolerance, while shifting toward damage-associated antigens during inflammation.

bioRxiv · Mar 20, 2026 · PreprintImmunology

Genesis: A Modular Protein Language Modelling Approach to Immunogenicity Prediction

Hugh O’Brien, Max Salm, Laura T. Morton, Maciej J. Szukszto, Felix O’Farrell, Charlotte Boulton, Laurence King, Supreet Kaur Bola, Pablo Daniel Becker, Andrew Craig, Morten Nielsen, Yardena Samuels, Charles Swanton, Marc R. Mansour, Sine Reker Hadrup, Sergio A. Quezada

Genesis is a modular protein language model that improves immunogenicity prediction for CD8+ epitopes by integrating pMHC and TCR context, outperforming existing models in precision.

bioRxiv · May 22, 2024 · PreprintBioinformatics

PhISCS-BnB: A Fast Branch and Bound Algorithm for the Perfect Tumor Phylogeny Reconstruction Problem

Erfan Sadeqi Azer, Farid Rashidi Mehrabadi, Salem Malikić, Xuan Cindy Li, Osnat Bartok, Kevin Litchfield, Ronen Levy, Yardena Samuels, Alejandro A. Schäffer, Edward Michael Gertz, Chi‐Ping Day, Eva Pérez‐Guijarro, Kerrie L. Marie, Maxwell P. Lee, Glenn T Merlino, , S. Cenk Şahinalp

PhISCS-BnB computes the most likely perfect tumor phylogeny from single-cell sequencing data, offering optimality guarantees and significant speed improvements over existing methods.

Bioinformatics · Jul 1, 2020Peer-reviewedBioinformatics