Fully differentiable coarse-grained and all-atom knowledge-based potentials for RNA structure evaluation

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Fully differentiable coarse-grained and all-atom knowledge-based potentials for RNA structure evaluation is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1261/RNA.2543711
P932PMC publication ID3096039
P698PubMed publication ID21521828
P5875ResearchGate publication ID51078653

P50authorMichael LevittQ6832227
Xuhui HuangQ30504212
Julie BernauerQ57200157
P2093author name stringAdelene Y L Sim
P2860cites workA probabilistic model of RNA conformational spaceQ21145357
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Consistent refinement of submitted models at CASP using a knowledge-based potentialQ28286468
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Solvent dramatically affects protein structure refinement.Q30373863
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RNA backbone is rotamericQ31024059
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Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability predictionQ38270534
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An accurate, residue-level, pair potential of mean force for folding and binding based on the distance-scaled, ideal-gas reference state.Q41833277
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Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins.Q52451138
Replica-exchange molecular dynamics method for protein foldingQ55879366
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Using a hydrophobic contact potential to evaluate native and near-native folds generated by molecular dynamics simulationsQ71121760
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Finite Mixture ModelsQ112113996
P433issue6
P407language of work or nameEnglishQ1860
P304page(s)1066-1075
P577publication date2011-04-26
P1433published inRNAQ7277164
P1476titleFully differentiable coarse-grained and all-atom knowledge-based potentials for RNA structure evaluation
P478volume17

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