Author

D. S. Shcherbinin

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Research Focus:protein folding & dynamics· 1 Assay:protein structure· 1

Frequent Co-Authors

M. Shugay· 2 shared A. O. Chugunov· 1 shared A. Simmons· 1 shared C. H.-J. Lee· 1 shared D. M. Chudakov· 1 shared H. Koohy· 1 shared I. V. Zvyagin· 1 shared I. Woodhouse· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersImmunology

M. Shugay

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Author profile →

2 papers

Recent·Most cited

TCRen: predicting TCR recognition of unseen epitopes based on residue-level pairwise statistical potential

V. K. Karnaukhov, D. S. Shcherbinin, A. O. Chugunov, D. M. Chudakov, R. G. Efremov, I. V. Zvyagin, M. Shugay

TCRen predicts TCR recognition of unseen epitopes using residue-level pairwise statistical potential from TCR-peptide contacts in crystal structures.

bioRxiv · Feb 15, 2022 · PreprintImmunology

Evaluating performance of existing computational models in predicting CD8+ T cell pathogenic epitopes and cancer neoantigens

P. Buckley, R. Ma, C. H.-J. Lee, I. Woodhouse, J. Woo, V. O. Tsvetkov, D. S. Shcherbinin, M. Shugay, M. Rei, A. Simmons, H. Koohy

This study evaluates existing computational models for predicting CD8+ T cell epitopes and cancer neoantigens, finding poor performance for emerging viruses and cancer peptides.

bioRxiv · Dec 25, 2020Immunology