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SCONES: Self-Consistent Neural Network for Protein Stabilit..:

Yashas B. L. Samaga (11461531) ; Shampa Raghunathan (1736623) ; U. Deva Priyakumar (480753)
https://figshare.com/articles/journal_contribution/SCONES_Self-Consistent_Neural_Network_for_Protein_Stability_Prediction_Upon_Mutation/16652365. , 2021

Link: https://doi.org/10.1021/acs.jpcb.1c04913.s001

RT Journal
T1 <Title>SCONES: Self-Consistent Neural Network for Protein Stability Prediction Upon Mutation</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_16652365&Exemplar=1&LAN=DE
				
A1 Yashas B. L. Samaga (11461531)
A1 Shampa Raghunathan (1736623)
A1 U. Deva Priyakumar (480753)
YR 2021
K1 Biophysics
K1 Biochemistry
K1 Genetics
K1 Molecular Biology
K1 Immunology
K1 Infectious Diseases
K1 Plant Biology
K1 Biological Sciences not elsewhere classified
K1 Mathematical Sciences not elsewhere classified
K1 Information Systems not elsewhere classified
K1 mutating amino acids
K1 many common biases
K1 local structural environment
K1 interpretable neural network
K1 independently predicted contributions
K1 engineered proteins must
K1 consistent neural network
K1 hypothetical reverse mutations
K1 transitive </ sup
K1 evaluating transitive consistency
K1 experimental methods used
K1 transitive properties
K1 missense mutations
K1 g </
K1 experimental data
K1 throughputs required
K1 symmetric consistency
K1 substantial portion
K1 specific sites
K1 significantly alter
K1 residue '
K1 relies less
K1 mutant residues
K1 existing methods
K1 determine stability
K1 desired properties
JF https://figshare.com/articles/journal_contribution/SCONES_Self-Consistent_Neural_Network_for_Protein_Stability_Prediction_Upon_Mutation/16652365
LK http://dx.doi.org/https://doi.org/10.1021/acs.jpcb.1c04913.s001
DO https://doi.org/10.1021/acs.jpcb.1c04913.s001
SF ELIB - SuUB Bremen

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