Author

M. A. Newton

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· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Assay:proteomics· 1

Frequent Co-Authors

A. Gitter· 1 shared C. L. Zuleger· 1 shared C.-p. Lee· 1 shared F. M. Hoffmann· 1 shared G. E. Ananiev· 1 shared H. Zhang· 1 shared J. C. Mitchell· 1 shared M. R. Albertini· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperPharmacology & Toxicology

A. Gitter

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2 papers

Recent·Most cited

ImmunologybioRxivJul 13, 2023

Surrogate selection oversamples expanded T cell clonotypes

P. Yu, Y. Lian, C. L. Zuleger…·M. A. Newton

The paper develops a model to quantify how surrogate selection assays may enrich for amplified T cell clones and explores its implications for immunological data analysis.

DOI 10.1214/25-aoas2032

humanscRNA-seq

𝕏 PostBluesky

Pharmacology & ToxicologybioRxivJan 28, 2019

Predicting kinase inhibitors using bioactivity matrix derived informer sets

H. Zhang, S. S. Ericksen, C.-p. Lee…·M. A. Newton

The paper develops an informer-based ranking method to predict kinase inhibitor activity using chemogenomic data, outperforming traditional chemical diversity-based approaches in both retrospective and prospective tests.

DOI 10.1371/journal.pcbi.1006813

proteomicsdeep learning

𝕏 PostBluesky