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FCHL revisited: Faster and more accurate quantum machine learning

The Journal of chemical physics, 2020-01, Vol.152 (4), p.044107-044107

2020

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Training Neural Nets To Learn Reactive Potential Energy Surfaces Using Interactive Quantum Chemistry in Virtual Reality

The journal of physical chemistry. A, Molecules, spectroscopy, kinetics, environment, & general theory, 2019-05, Vol.123 (20), p.4486-4499

2019

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Low dimensional representations along intrinsic reaction coordinates and molecular dynamics trajectories using interatomic distance matrices

Chemical science (Cambridge), 2019-11, Vol.1 (43), p.9954-9968

2019

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A community-powered search of machine learning strategy space to find NMR property prediction models

PloS one, 2021-07, Vol.16 (7), p.e0253612-e0253612

2021

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IMPRESSION - prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy

Chemical science (Cambridge), 2020-01, Vol.11 (2), p.58-515

2020

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ProCS15: a DFT-based chemical shift predictor for backbone and Cβ atoms in proteins

PeerJ (San Francisco, CA), 2015-10, Vol.3, p.e1344-e1344, Article e1344

2015

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Bayesian inference of protein structure from chemical shift data

PeerJ (San Francisco, CA), 2015-03, Vol.3, p.e861-e861

2015

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Protein structure refinement using a quantum mechanics-based chemical shielding predictor

Chemical science (Cambridge), 2017-03, Vol.8 (3), p.2061-2072

2017

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Protein structure refinement using a quantum mechanics-based chemical shielding predictorElectronic supplementary information (ESI) available. See DOI: 10.1039/c6sc04344e

2017-02

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Protein structure refinement using a quantum mechanics-based chemical shielding predictor† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6sc04344e Click here for additional data file

Chemical science (Cambridge), 2016-12, Vol.8 (3), p.2061-2072

2016

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Low dimensional representations along intrinsic reaction coordinates and molecular dynamics trajectories using interatomic distance matrices† †Electronic supplementary information (ESI) available: The ESI contains the following input xyz files and PathReducer output xyz files, for mass-weighted and not mass-weighted coordinates and for both “Cartesians” and “Distances” inputs to PCA: (1) input files: (a) malonaldehyde system IRC, (b) SN2 system (i) IRC (ii) MD trajectory, (c) N2O–acrylonitrile s

Chemical science (Cambridge), 2019-09, Vol.10 (43), p.9954-9968

2019

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IMPRESSION – prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c9sc03854j

Chemical science (Cambridge), 2019-11, Vol.11 (2), p.508-515

2019

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ProCS15: a DFT-based chemical shift predictor for backbone and C[beta] atoms in proteins

PeerJ (San Francisco, CA), 2015-10, Vol.3, p.e1344

2015

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Functional evidence of low-pressure cardiopulmonary baroreceptor reinnervation 1 year after heart transplantation

European journal of applied physiology, 2021-03, Vol.121 (3), p.915-927

2021

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Autonomic cardiovascular control changes in recent heart transplant recipients lead to physiological limitations in response to orthostatic challenge and isometric exercise

European journal of applied physiology, 2019-10, Vol.119 (10), p.2225-2236

2019

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Simultaneous determination of glucose, triglycerides, urea, cholesterol, albumin and total protein in human plasma by Fourier transform infrared spectroscopy: Direct clinical biochemistry without reagents

Clinical biochemistry, 2014-09, Vol.47 (13-14), p.1306-1312

2014

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Automated Fragmentation Polarizable Embedding Density Functional Theory (PE-DFT) Calculations of Nuclear Magnetic Resonance (NMR) Shielding Constants of Proteins with Application to Chemical Shift Predictions

Journal of chemical theory and computation, 2017-02, Vol.13 (2), p.525-536

2017

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Strong evidence for parasympathetic sinoatrial reinnervation after heart transplantation

The Journal of heart and lung transplantation, 2022-07, Vol.41 (7), p.898-909

2022

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Factors Associated With Sinoatrial Reinnervation After Heart Transplantation

Transplantation direct, 2023-12, Vol.9 (12), p.e1553-e1553

2023

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FCHL revisited: Faster and more accurate quantum machine learning

Training Neural Nets To Learn Reactive Potential Energy Surfaces Using Interactive Quantum Chemistry in Virtual Reality

Low dimensional representations along intrinsic reaction coordinates and molecular dynamics trajectories using interatomic distance matrices

A community-powered search of machine learning strategy space to find NMR property prediction models

IMPRESSION - prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy

ProCS15: a DFT-based chemical shift predictor for backbone and Cβ atoms in proteins

Bayesian inference of protein structure from chemical shift data

Protein structure refinement using a quantum mechanics-based chemical shielding predictor

Protein structure refinement using a quantum mechanics-based chemical shielding predictorElectronic supplementary information (ESI) available. See DOI: 10.1039/c6sc04344e

Protein structure refinement using a quantum mechanics-based chemical shielding predictor† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6sc04344e Click here for additional data file

IMPRESSION – prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c9sc03854j

ProCS15: a DFT-based chemical shift predictor for backbone and C[beta] atoms in proteins

Functional evidence of low-pressure cardiopulmonary baroreceptor reinnervation 1 year after heart transplantation

Autonomic cardiovascular control changes in recent heart transplant recipients lead to physiological limitations in response to orthostatic challenge and isometric exercise

Simultaneous determination of glucose, triglycerides, urea, cholesterol, albumin and total protein in human plasma by Fourier transform infrared spectroscopy: Direct clinical biochemistry without reagents

Automated Fragmentation Polarizable Embedding Density Functional Theory (PE-DFT) Calculations of Nuclear Magnetic Resonance (NMR) Shielding Constants of Proteins with Application to Chemical Shift Predictions

Strong evidence for parasympathetic sinoatrial reinnervation after heart transplantation

Factors Associated With Sinoatrial Reinnervation After Heart Transplantation

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