Author

Miriam Müller

La Jolla Institute for Immunology

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

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Immunology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:proteomics· 1

Frequent Co-Authors

Alessandro SetteiD· 1 shared Bjoern PetersiD· 1 shared Cecilia S. Lindestam ArlehamniD· 1 shared Daniel MarramaiD· 1 shared Ehdieh KhaledianiD· 1 shared Hannah BatteyiD· 1 shared Ricardo da Silva AntunesiD· 1 shared Sudhasini PandaiD· 1 shared

Activity by Year

2024-2024 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperImmunology

Alessandro SetteORCID

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1 paper

Recent·Most cited

Predicting Immunogenic CD4+ T Cell Epitopes in Bacteria Using Antigen and Peptide Features

Daniel Marrama, Hannah Battey, Ehdieh Khaledian, Miriam Müller, Sudhasini Panda, Ricardo da Silva Antunes, Alessandro Sette, Cecilia S. Lindestam Arlehamn, Bjoern Peters

This paper develops a machine learning model that integrates peptide and antigen features to predict immunogenic CD4+ T cell epitopes in bacteria, achieving high accuracy across multiple bacterial species.

bioRxiv · Oct 25, 2024 · PreprintImmunology