Author

A. Krishnakumar

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

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:protein structure· 2 Approach:contrastive learning· 1 Organism:human· 1 Research Focus:protein folding & dynamics· 1 Research Focus:protein structure prediction· 1 Organism:yeast· 1

Frequent Co-Authors

D. Baker· 2 shared I. Anishchenko· 2 shared I. R. Humphreys· 2 shared J. Pei· 2 shared M. Baek· 2 shared Q. Cong· 2 shared B. A. Jackson· 1 shared B. Szakal· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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2 shared papersBiochemistry

D. Baker

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2 papers

Recent·Most cited

Essential and virulence-related protein interactions of pathogens revealed through deep learning

I. R. Humphreys, J. Zhang, M. Baek, Y. Wang, A. Krishnakumar, J. Pei, I. Anishchenko, C. A. Tower, B. A. Jackson, T. Warrier, D. T. Hung, S. B. Peterson, J. D. Mougous, Q. Cong, D. Baker

This study uses deep learning to predict protein-protein interactions in bacterial pathogens, identifying new complexes involving essential genes and virulence factors, with half of tested predictions validated.

bioRxiv · Apr 12, 2024 · PreprintBiochemistry

Structures of core eukaryotic protein complexes

I. R. Humphreys, J. Pei, M. Baek, A. Krishnakumar, I. Anishchenko, S. R. Ovchinnikov, J. Zheng, T. Ness, S. Banjade, S. R. Bagde, V. Stancheva, X. Li, K. Liu, Z. Zheng, D. Barerro, , D. Baker

The paper uses coevolution analysis and deep learning to model core eukaryotic protein complexes in yeast, identifying 104 new assemblies and structurally characterizing 608 previously unknown complexes.

bioRxiv · Sep 30, 2021Biochemistry