Author

S. N. Yaliraki

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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Research Focus:protein folding & dynamics· 2 Approach:deep learning· 1 Approach:graph neural network· 1 Approach:mechanistic / dynamical model· 1 Assay:protein structure· 1

Frequent Co-Authors

M. Barahona· 2 shared D. R. Klug· 1 shared D. Saman· 1 shared K. R. Willison· 1 shared L. Ying· 1 shared M. Hodges· 1 shared R. L. Peach· 1 shared

Activity by Year

2019-2019 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 16 mutual co-author links

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2 shared papersBiophysics

M. Barahona

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2 papers

Recent·Most cited

BiophysicsbioRxivPreprintNov 20, 2019

Unsupervised graph-based learning predicts mutations that alter protein dynamics

R. L. Peach, D. Saman, S. N. Yaliraki…·M. Barahona

The paper uses graph-based learning to predict mutations affecting protein dynamics, validated by FRET experiments on adenylate kinase.

DOI 10.1101/847426

protein structuredeep learning

𝕏 PostBluesky

BiophysicsbioRxivNov 15, 2019

An edge-based formulation of elastic network models

M. Hodges, S. N. Yaliraki, M. Barahona

This paper introduces an edge-based formulation for elastic network models to study mechanical interactions, demonstrating its application to protein systems.

DOI 10.1103/physrevresearch.1.033211

mechanistic / dynamical modelprotein folding & dynamics

𝕏 PostBluesky