Author

Murali Anuganti

Institute for Protein InnovationORCID 0000-0002-9023-450XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Biophysics· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Approach:machine learning (classical)· 2 Assay:proteomics· 2 Organism:human· 1 Organism:mouse· 1

Frequent Co-Authors

Aaron W. KollaschiD· 2 shared Andre A. R. TeixeiraiD· 2 shared Debora S. MarksiD· 2 shared Deborah J. MoshinskyiD· 2 shared Filmawit Belay· 2 shared Haisun ZhuiD· 2 shared Steffan B. PauliD· 2 shared Adam J. RiesselmaniD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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2 shared papersBiophysics

Aaron W. KollaschORCID

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2 papers

Recent·Most cited

BiophysicsCell SystemsPeer-reviewedJun 23, 2026

High-Throughput Machine Learning-Aided Antibody Discovery for Cell Surface Antigens

Deepash Kothiwal, Aaron W. Kollasch, Murali Anuganti…·Rob Meijers

The paper develops a synthetic Fab yeast display library integrated with machine learning to discover antibodies against cell surface antigens, yielding hundreds of validated antibodies and a public dataset.

1 citation

humanmouse

𝕏 PostBluesky

BioinformaticsbioRxivPreprintJan 12, 2026

Machine Learning enables efficient and effective affinity maturation of nanobodies

Steffan B. Paul, Edward P. Harvey, James Osei‐Owusu…·Andrew C. Kruse

This paper uses machine learning to predict high-affinity nanobody binders from sparse sequencing data, outperforming deep learning and semi-supervised methods with linear models.

2 citations

proteomicsmachine learning (classical)

𝕏 PostBluesky