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Journal of Chemical Theory and Computation|November 19, 2024
Bayesian Approach for Computing Free Energy on Perturbation Graphs with CyclesXinqiang Ding, John DrohanThe Journal of Physical Chemistry. B|July 5, 2024
Optimizing Force Fields with Experimental Data Using Ensemble Reweighting and Potential ContrastingXinqiang DingJournal of Chemical Theory and Computation|February 22, 2024
Bayesian Multistate Bennett Acceptance Ratio MethodsXinqiang DingJournal of Chemical Theory and Computation|September 16, 2022
Contrastive Learning of Coarse-Grained Force FieldsXinqiang Ding, Bin ZhangThe Journal of Physical Chemistry. B|November 4, 2020
Computing Absolute Free Energy with Deep Generative ModelsXinqiang Ding, Bin ZhangThe Journal of Physical Chemistry Letters|March 15, 2021
DeepBAR: A Fast and Exact Method for Binding Free Energy ComputationXinqiang Ding, Bin ZhangBiorxiv : the Preprint Server for Biology|September 25, 2023
Transferable Coarse Graining via Contrastive Learning of Graph Neural NetworksJustin Airas, Xinqiang Ding, Bin ZhangBiophysical Journal|July 27, 2023
Efficient Hi-C inversion facilitates chromatin folding mechanism discovery and structure predictionGreg Schuette, Xinqiang Ding, Bin ZhangNature Communications|February 18, 2021
Stability and folding pathways of tetra-nucleosome from six-dimensional free energy surfaceXinqiang Ding, Xingcheng Lin, Bin ZhangBiorxiv : the Preprint Server for Biology|March 30, 2023
Efficient Hi-C inversion facilitates chromatin folding mechanism discovery and structure predictionGreg Schuette, Xinqiang Ding, Bin ZhangPageof 3