Author

R. Ranganathan

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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Biochemistry· 2 Biophysics· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Research Focus:protein folding & dynamics· 3 Assay:protein sequence· 2 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Research Focus:protein design· 1 Assay:structural biology· 1

Frequent Co-Authors

W. P. Russ· 2 shared C. Stocker· 1 shared D. Hilvert· 1 shared E. Klyshko· 1 shared E. Lee· 1 shared J. S.-H. Kim· 1 shared L. McGough· 1 shared M. Figliuzzi· 1 shared

Activity by Year

2017-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersBiophysics

W. P. Russ

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4 papers

Recent·Most cited

Functional Protein Dynamics in a Crystal

E. Klyshko, J. S.-H. Kim, L. McGough, V. Valeeva, E. Lee, R. Ranganathan, S. Rauscher

This paper develops methods to simulate protein dynamics in crystals and shows they accurately capture ligand-induced conformational changes.

bioRxiv · Jul 6, 2023Biophysics

Undersampling and the inference of coevolution in proteins

Y. Kleeorin, W. P. Russ, O. Rivoire, R. Ranganathan

This paper shows that current methods for inferring protein coevolution are biased due to undersampling and scale mismatches in epistatic interactions.

bioRxiv · Apr 22, 2021Biophysics

Evolution-based design of chorismate mutase enzymes

W. P. Russ, M. Figliuzzi, C. Stocker, P. Barrat-Charlaix, M. Socolich, P. Kast, D. Hilvert, R. Monasson, S. Cocco, M. Weigt, R. Ranganathan

This paper demonstrates an evolution-based design process for synthetic enzymes using sequence data, showing that statistical models can generate functional sequences with substantial diversity.

bioRxiv · Apr 1, 2020 · PreprintBiochemistry

Inferring amino acid interactions underlying protein function

V. H. Salinas, R. Ranganathan

The paper measures pairwise amino acid interactions in homologous proteins using deep-mutation technologies and shows conserved cooperative networks despite evolutionary divergence.

bioRxiv · Nov 7, 2017Biochemistry