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Jie (Jerry) Li - Publications

Affiliations: 
Chemistry University of California, Berkeley, Berkeley, CA, United States 
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17 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2024 Li J, Liang J, Wang Z, Ptaszek AL, Liu X, Ganoe B, Head-Gordon M, Head-Gordon T. Highly Accurate Prediction of NMR Chemical Shifts from Low-Level Quantum Mechanics Calculations Using Machine Learning. Journal of Chemical Theory and Computation. PMID 38331423 DOI: 10.1021/acs.jctc.3c01256  0.556
2023 Liu ZH, Teixeira JMC, Zhang O, Tsangaris TE, Li J, Gradinaru CC, Head-Gordon T, Forman-Kay JD. Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments. Bioinformatics (Oxford, England). PMID 38060268 DOI: 10.1093/bioinformatics/btad739  0.488
2023 Li J, Guan X, Zhang O, Sun K, Wang Y, Bagni D, Head-Gordon T. Leak Proof PDBBind: A Reorganized Dataset of Protein-Ligand Complexes for More Generalizable Binding Affinity Prediction. Arxiv. PMID 37645037  0.483
2023 Liu ZH, Teixeira JMC, Zhang O, Tsangaris TE, Li J, Gradinaru CC, Head-Gordon T, Forman-Kay JD. Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments. Biorxiv : the Preprint Server For Biology. PMID 37546943 DOI: 10.1101/2023.07.25.550520  0.49
2023 Zhang O, Haghighatlari M, Li J, Liu ZH, Namini A, Teixeira JMC, Forman-Kay JD, Head-Gordon T. Learning to evolve structural ensembles of unfolded and disordered proteins using experimental solution data. The Journal of Chemical Physics. 158. PMID 37144719 DOI: 10.1063/5.0141474  0.513
2023 Wong J, Ganoe B, Liu X, Neudecker T, Lee J, Liang J, Wang Z, Li J, Rettig A, Head-Gordon T, Head-Gordon M. An in-silico NMR laboratory for nuclear magnetic shieldings computed via finite fields: Exploring nucleus-specific renormalizations of MP2 and MP3. The Journal of Chemical Physics. 158. PMID 37114707 DOI: 10.1063/5.0145130  0.481
2023 Li J, Zhang O, Lee S, Namini A, Liu ZH, Teixeira JMC, Forman-Kay JD, Head-Gordon T. Learning Correlations between Internal Coordinates to Improve 3D Cartesian Coordinates for Proteins. Journal of Chemical Theory and Computation. PMID 36749957 DOI: 10.1021/acs.jctc.2c01270  0.519
2023 Liang J, Wang Z, Li J, Wong J, Liu X, Ganoe B, Head-Gordon T, Head-Gordon M. Efficient Calculation of NMR Shielding Constants Using Composite Method Approximations and Locally Dense Basis Sets. Journal of Chemical Theory and Computation. PMID 36594660 DOI: 10.1021/acs.jctc.2c00933  0.476
2022 Teixeira JMC, Liu ZH, Namini A, Li J, Vernon RM, Krzeminski M, Shamandy AA, Zhang O, Haghighatlari M, Yu L, Head-Gordon T, Forman-Kay JD. IDPConformerGenerator: A Flexible Software Suite for Sampling the Conformational Space of Disordered Protein States. The Journal of Physical Chemistry. A. PMID 36030416 DOI: 10.1021/acs.jpca.2c03726  0.496
2022 Haghighatlari M, Li J, Guan X, Zhang O, Das A, Stein CJ, Heidar-Zadeh F, Liu M, Head-Gordon M, Bertels L, Hao H, Leven I, Head-Gordon T. NewtonNet: a Newtonian message passing network for deep learning of interatomic potentials and forces. Digital Discovery. 1: 333-343. PMID 35769203 DOI: 10.1039/d2dd00008c  0.707
2022 Guan X, Das A, Stein CJ, Heidar-Zadeh F, Bertels L, Liu M, Haghighatlari M, Li J, Zhang O, Hao H, Leven I, Head-Gordon M, Head-Gordon T. A benchmark dataset for Hydrogen Combustion. Scientific Data. 9: 215. PMID 35581204 DOI: 10.1038/s41597-022-01330-5  0.702
2022 Naullage PM, Haghighatlari M, Namini A, Teixeira JMC, Li J, Zhang O, Gradinaru CC, Forman-Kay JD, Head-Gordon T. Protein Dynamics to Define and Refine Disordered Protein Ensembles. The Journal of Physical Chemistry. B. PMID 35213160 DOI: 10.1021/acs.jpcb.1c10925  0.476
2021 Stauch T, Ganoe B, Wong J, Lee J, Rettig A, Liang J, Li J, Epifanovsky E, Head-Gordon T, Head-Gordon M. Molecular Magnetizabilities Computed Via Finite Fields: Assessing Alternatives to MP2 and Revisiting Magnetic Exaltations in Aromatic and Antiaromatic Species. Molecular Physics. 119. PMID 35264815 DOI: 10.1080/00268976.2021.1990426  0.482
2021 Wang X, Li J, Ha HD, Dahl JC, Ondry JC, Moreno-Hernandez I, Head-Gordon T, Alivisatos AP. AutoDetect-mNP: An Unsupervised Machine Learning Algorithm for Automated Analysis of Transmission Electron Microscope Images of Metal Nanoparticles. Jacs Au. 1: 316-327. PMID 33778811 DOI: 10.1021/jacsau.0c00030  0.452
2020 Li J, Bennett KC, Liu Y, Martin MV, Head-Gordon T. Accurate prediction of chemical shifts for aqueous protein structure on "Real World" data. Chemical Science. 11: 3180-3191. PMID 34122823 DOI: 10.1039/c9sc06561j  0.728
2020 Haghighatlari M, Li J, Heidar-Zadeh F, Liu Y, Guan X, Head-Gordon T. Learning to Make Chemical Predictions: the Interplay of Feature Representation, Data, and Machine Learning Methods. Chem. 6: 1527-1542. PMID 32695924 DOI: 10.1016/J.Chempr.2020.05.014  0.576
2019 Liu S, Li J, Bennett K, Ganoe B, Stauch T, Head-Gordon M, Hexemer A, Ushizima D, Head-Gordon T. A Multi-Resolution 3D-DenseNet for Chemical Shift Prediction in NMR Crystallography. The Journal of Physical Chemistry Letters. PMID 31305081 DOI: 10.1021/Acs.Jpclett.9B01570  0.73
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