Author

Michael Urbakh

Tel Aviv UniversityORCID 0000-0002-3959-5414Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:protein folding & dynamics· 1

Frequent Co-Authors

Shlomi ReuveniiD· 2 shared Divya Prakash SinghiD· 1 shared Divya SinghiD· 1 shared Tal RobiniD· 1 shared

Activity by Year

2025-2025 · peak 2/yr

Co-Author Collaboration Network

4 top collaborators · 4 mutual co-author links

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2 shared papersBiophysics

Shlomi ReuveniORCID

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2 papers

Recent·Most cited

BiophysicsNature CommunicationsPeer-reviewedMar 20, 2025

High-order Michaelis-Menten equations allow inference of hidden kinetic parameters in enzyme catalysis

Divya Singh, Tal Robin, Michael Urbakh, Shlomi Reuveni

The paper derives high-order Michaelis-Menten equations to infer hidden kinetic parameters in enzyme catalysis from single-molecule data.

19 citationstop 2%

statistical model

𝕏 PostBluesky

BiophysicsbioRxivPreprintFeb 4, 2025

Inferring binding rates from enzymatic turnover time statistics

Divya Prakash Singh, Michael Urbakh, Shlomi Reuveni

This paper introduces a method to infer enzyme-substrate binding rates and related probabilities from enzymatic turnover time statistics, enabling a more detailed understanding of enzymatic efficiency.

2 citations

statistical modelprotein folding & dynamics

𝕏 PostBluesky