Author

N. Spisak

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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Immunology· 4

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 4 Approach:statistical model· 4 Research Focus:differential expression· 3 Organism:human· 3 Assay:CITE-seq· 2 Research Focus:clustering· 2 Research Focus:gene regulatory network inference· 2 Approach:deep learning· 1

Frequent Co-Authors

T. Mora· 4 shared A. M. Walczak· 3 shared A. Beyer· 1 shared A. Nourmohammad· 1 shared A. Walczak· 1 shared C. Kreer· 1 shared C. Lupo· 1 shared F. Klein· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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4 shared papersImmunology

T. Mora

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4 papers

Recent·Most cited

Combining mutation and recombination statistics to infer clonal families in antibody repertoires

N. Spisak, T. Dupic, T. Mora, A. M. Walczak

The paper introduces HILARy, a method to identify clonal families in antibody repertoires by combining mutation and recombination statistics, finding evolutionary properties are independent of junction length and revealing broad selection pressures.

bioRxiv · Dec 22, 2022Immunology

Probabilities of HIV-1 bNAb development in healthy and chronically infected individuals

C. Kreer, C. Lupo, M. S. Ercanoglu, L. Gieselmann, N. Spisak, J. Grossbach, M. Schlotz, P. Schommers, H. Gruell, L. Dold, A. Beyer, A. Nourmohammad, T. Mora, A. Walczak, F. Klein

The paper uses sequence analysis to predict the likelihood of HIV-1 broadly neutralizing antibody (bNAb) development in healthy and infected individuals, finding that chronic infection is not required for bNAb generation.

bioRxiv · Jul 11, 2022Immunology

Modeling and predicting the overlap of B- and T-cell receptor repertoires in healthy and SARS-CoV-2 infected individuals

M. Ruiz Ortega, N. Spisak, T. Mora, A. M. Walczak

The paper develops a statistical model to predict B- and T-cell receptor repertoire overlap in healthy and SARS-CoV-2 infected individuals, identifying COVID-associated receptors and designing a diagnostic tool.

bioRxiv · Dec 17, 2021 · PreprintImmunology

Learning the heterogeneous hypermutation landscape of immunoglobulins from high-throughput repertoire data

N. Spisak, A. M. Walczak, T. Mora

The paper develops a model to quantify hypermutation biases in Ig genes, revealing sequence context and position effects, and identifies co-localization of mutations in B-cell lineages.

bioRxiv · Jul 21, 2020Immunology