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Raghavachari

Showing results (51-60 of 305) with videos related to

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Journal of Chemical Theory and Computation|May 3, 2023
Interpretable Graph-Network-Based Machine Learning Models via Molecular FragmentationEric M Collins, Krishnan Raghavachari
Plos Computational Biology|November 1, 2008
The effects of NR2 subunit-dependent NMDA receptor kinetics on synaptic transmission and CaMKII activationDavid M Santucci, Sridhar Raghavachari
Accounts of Chemical Research|November 14, 2014
The successful merger of theoretical thermochemistry with fragment-based methods in quantum chemistryRaghunath O Ramabhadran, Krishnan Raghavachari
Journal of Chemical Theory and Computation|December 1, 2015
Charge Transfer Across ONIOM QM:QM Boundaries: The Impact of Model System PreparationNicholas J Mayhall, Krishnan Raghavachari
Geroscience|October 31, 2018
Report: NIA workshop on translating genetic variants associated with longevity into drug targetsNicholas J Schork, Nalini Raghavachari,
The Journal of Physical Chemistry. A|August 2, 2007
Two methanes are better than one: a density functional theory study of the reactions of Mo2Oy- (y = 2-5) with methaneNicholas J Mayhall, Krishnan Raghavachari
Journal of Chemical Theory and Computation|February 28, 2022
Three-Dimensional Convolutional Neural Networks Utilizing Molecular Topological Features for Accurate Atomization Energy PredictionsAnkur Kumar Gupta, Krishnan Raghavachari
Methods in Molecular Biology (Clifton, N.J.)|May 17, 2018
Overview of Gene Expression Analysis: TranscriptomicsNalini Raghavachari, Natàlia Garcia-Reyero
Journal of Chemical Theory and Computation|September 13, 2023
MIM-ML: A Novel Quantum Chemical Fragment-Based Random Forest Model for Accurate Prediction of NMR Chemical Shifts of Nucleic AcidsSruthy K Chandy, Krishnan Raghavachari
The Journal of Physical Chemistry. A|August 3, 2021
A Fragmentation-Based Graph Embedding Framework for QM/MLEric M Collins, Krishnan Raghavachari
Pageof 31

Showing results (51-60 of 305) with videos related to

Sort By:
Pageof 31
Journal of Chemical Theory and Computation|May 3, 2023
Interpretable Graph-Network-Based Machine Learning Models via Molecular FragmentationEric M Collins, Krishnan Raghavachari
Plos Computational Biology|November 1, 2008
The effects of NR2 subunit-dependent NMDA receptor kinetics on synaptic transmission and CaMKII activationDavid M Santucci, Sridhar Raghavachari
Accounts of Chemical Research|November 14, 2014
The successful merger of theoretical thermochemistry with fragment-based methods in quantum chemistryRaghunath O Ramabhadran, Krishnan Raghavachari
Journal of Chemical Theory and Computation|December 1, 2015
Charge Transfer Across ONIOM QM:QM Boundaries: The Impact of Model System PreparationNicholas J Mayhall, Krishnan Raghavachari
Geroscience|October 31, 2018
Report: NIA workshop on translating genetic variants associated with longevity into drug targetsNicholas J Schork, Nalini Raghavachari,
The Journal of Physical Chemistry. A|August 2, 2007
Two methanes are better than one: a density functional theory study of the reactions of Mo2Oy- (y = 2-5) with methaneNicholas J Mayhall, Krishnan Raghavachari
Journal of Chemical Theory and Computation|February 28, 2022
Three-Dimensional Convolutional Neural Networks Utilizing Molecular Topological Features for Accurate Atomization Energy PredictionsAnkur Kumar Gupta, Krishnan Raghavachari
Methods in Molecular Biology (Clifton, N.J.)|May 17, 2018
Overview of Gene Expression Analysis: TranscriptomicsNalini Raghavachari, Natàlia Garcia-Reyero
Journal of Chemical Theory and Computation|September 13, 2023
MIM-ML: A Novel Quantum Chemical Fragment-Based Random Forest Model for Accurate Prediction of NMR Chemical Shifts of Nucleic AcidsSruthy K Chandy, Krishnan Raghavachari
The Journal of Physical Chemistry. A|August 3, 2021
A Fragmentation-Based Graph Embedding Framework for QM/MLEric M Collins, Krishnan Raghavachari
Pageof 31