Search research articles
Contact Us
Filters
Showing results (1-10 of 30) with videos related to
Page
of 3
Sort By:
Current Opinion in Structural Biology
|
February 6, 2025
Protein ligand structure prediction: From empirical to deep learning approaches
Guangfeng Zhou, Frank DiMaio
The Journal of Physical Chemistry. B
|
January 16, 2016
Using Kinetic Network Models To Probe Non-Native Salt-Bridge Effects on α-Helix Folding
Guangfeng Zhou, Vincent A Voelz
Journal of Computational Chemistry
|
September 25, 2014
Bayesian inference of conformational state populations from computational models and sparse experimental observables
Vincent A Voelz, Guangfeng Zhou
Journal of Chemical Theory and Computation
|
December 14, 2016
A Maximum-Caliber Approach to Predicting Perturbed Folding Kinetics Due to Mutations
Hongbin Wan, Guangfeng Zhou, Vincent A Voelz
Biorxiv : the Preprint Server for Biology
|
November 28, 2024
Automated identification of small molecules in cryo-electron microscopy data with density- and energy-guided evaluation
Andrew Muenks, Daniel P Farrell, Guangfeng Zhou, et al.
The Journal of Physical Chemistry. B
|
November 20, 2015
Insights into Peptoid Helix Folding Cooperativity from an Improved Backbone Potential
Sudipto Mukherjee, Guangfeng Zhou, Chris Michel, et al.
Structure (London, England : 1993)
|
July 27, 2025
Automated identification of small molecules in cryoelectron microscopy data with density- and energy-guided evaluation
Andrew Muenks, Daniel P Farrell, Guangfeng Zhou, et al.
Journal of Chemical Theory and Computation
|
February 12, 2021
Force Field Optimization Guided by Small Molecule Crystal Lattice Data Enables Consistent Sub-Angstrom Protein-Ligand Docking
Hahnbeom Park, Guangfeng Zhou, Minkyung Baek, et al.
Nature Communications
|
March 1, 2023
Automatic and accurate ligand structure determination guided by cryo-electron microscopy maps
Andrew Muenks, Samantha Zepeda, Guangfeng Zhou, et al.
Journal of Chemical Theory and Computation
|
November 20, 2015
Surprisal Metrics for Quantifying Perturbed Conformational Dynamics in Markov State Models
Vincent A Voelz, Brandon Elman, Asghar M Razavi, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 30) with videos related to
Sort By:
Page
of 3
Current Opinion in Structural Biology
|
February 6, 2025
Protein ligand structure prediction: From empirical to deep learning approaches
Guangfeng Zhou, Frank DiMaio
The Journal of Physical Chemistry. B
|
January 16, 2016
Using Kinetic Network Models To Probe Non-Native Salt-Bridge Effects on α-Helix Folding
Guangfeng Zhou, Vincent A Voelz
Journal of Computational Chemistry
|
September 25, 2014
Bayesian inference of conformational state populations from computational models and sparse experimental observables
Vincent A Voelz, Guangfeng Zhou
Journal of Chemical Theory and Computation
|
December 14, 2016
A Maximum-Caliber Approach to Predicting Perturbed Folding Kinetics Due to Mutations
Hongbin Wan, Guangfeng Zhou, Vincent A Voelz
Biorxiv : the Preprint Server for Biology
|
November 28, 2024
Automated identification of small molecules in cryo-electron microscopy data with density- and energy-guided evaluation
Andrew Muenks, Daniel P Farrell, Guangfeng Zhou, et al.
The Journal of Physical Chemistry. B
|
November 20, 2015
Insights into Peptoid Helix Folding Cooperativity from an Improved Backbone Potential
Sudipto Mukherjee, Guangfeng Zhou, Chris Michel, et al.
Structure (London, England : 1993)
|
July 27, 2025
Automated identification of small molecules in cryoelectron microscopy data with density- and energy-guided evaluation
Andrew Muenks, Daniel P Farrell, Guangfeng Zhou, et al.
Journal of Chemical Theory and Computation
|
February 12, 2021
Force Field Optimization Guided by Small Molecule Crystal Lattice Data Enables Consistent Sub-Angstrom Protein-Ligand Docking
Hahnbeom Park, Guangfeng Zhou, Minkyung Baek, et al.
Nature Communications
|
March 1, 2023
Automatic and accurate ligand structure determination guided by cryo-electron microscopy maps
Andrew Muenks, Samantha Zepeda, Guangfeng Zhou, et al.
Journal of Chemical Theory and Computation
|
November 20, 2015
Surprisal Metrics for Quantifying Perturbed Conformational Dynamics in Markov State Models
Vincent A Voelz, Brandon Elman, Asghar M Razavi, et al.
Page
of 3