Author

Friedrich Rippmann

Merck KGaA, Darmstadt (Germany)ORCID 0000-0002-4604-9251Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1 Assay:protein sequence· 1 Research Focus:sequence-to-function modeling· 1 Approach:statistical model· 1

Frequent Co-Authors

Ahmad NajafianiD· 1 shared Alejandro Crespo· 1 shared Andreas EversiD· 1 shared Daniel KühniD· 1 shared Maria BorisovskaiD· 1 shared Shipra MalhotraiD· 1 shared Shira Warszawski· 1 shared Vanita D. SoodiD· 1 shared

Activity by Year

2022-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Ahmad NajafianORCID

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1 paper

Recent·Most cited

SUMO - In Silico Sequence Assessment Using Multiple Optimization Parameters

Andreas Evers, Shipra Malhotra, Wolf-Guido Bolick, Ahmad Najafian, Maria Borisovska, Shira Warszawski, Yves Fomekong‐Nanfack, Daniel Kühn, Friedrich Rippmann, Alejandro Crespo, Vanita D. Sood

The paper introduces a computational method to assess and rank antibody and VHH sequences based on developability, diversity, and optimization potential using in silico analysis.

bioRxiv · Nov 19, 2022 · PreprintBioinformatics

Friedrich Rippmann · henhao