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Sumant R Shringari

Showing results (1-10 of 4) with videos related to

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Chemical Communications (Cambridge, England)|August 27, 2020
Correction: Rosetta custom score functions accurately predict ΔΔG of mutations at protein-protein interfaces using machine learningSumant R Shringari, Sam Giannakoulias, John J Ferrie, et al.
Scientific Reports|September 16, 2021
Biomolecular simulation based machine learning models accurately predict sites of tolerability to the unnatural amino acid acridonylalanineSam Giannakoulias, Sumant R Shringari, John J Ferrie, et al.
Chemical Communications (Cambridge, England)|May 23, 2020
Rosetta custom score functions accurately predict ΔΔG of mutations at protein-protein interfaces using machine learningSumant R Shringari, Sam Giannakoulias, John J Ferrie, et al.
The Journal of Physical Chemistry. B|September 2, 2020
Rosetta Machine Learning Models Accurately Classify Positional Effects of Thioamides on ProteolysisSam Giannakoulias, Sumant R Shringari, Chunxiao Liu, et al.
Pageof 1

Showing results (1-10 of 4) with videos related to

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Pageof 1
Chemical Communications (Cambridge, England)|August 27, 2020
Correction: Rosetta custom score functions accurately predict ΔΔG of mutations at protein-protein interfaces using machine learningSumant R Shringari, Sam Giannakoulias, John J Ferrie, et al.
Scientific Reports|September 16, 2021
Biomolecular simulation based machine learning models accurately predict sites of tolerability to the unnatural amino acid acridonylalanineSam Giannakoulias, Sumant R Shringari, John J Ferrie, et al.
Chemical Communications (Cambridge, England)|May 23, 2020
Rosetta custom score functions accurately predict ΔΔG of mutations at protein-protein interfaces using machine learningSumant R Shringari, Sam Giannakoulias, John J Ferrie, et al.
The Journal of Physical Chemistry. B|September 2, 2020
Rosetta Machine Learning Models Accurately Classify Positional Effects of Thioamides on ProteolysisSam Giannakoulias, Sumant R Shringari, Chunxiao Liu, et al.
Pageof 1