MedusaDock 2.0: Efficient and Accurate Protein-Ligand Docking With Constraints. - Jian Wang 094; Nikolay V. Dokholyan (J. Chem. Inf. Model., 2019)

Guiding Conventional Protein-Ligand Docking Software with Convolutional Neural Networks. - Huaipan Jiang; Mengran Fan; Jian Wang 094; Anup Sarma; Shruti Mohanty; Nikolay V. Dokholyan; Mehrdad Mahdavi; Mahmut T. Kandemir (J. Chem. Inf. Model., 2020)

Invited: Drug Discovery Approaches using Quantum Machine Learning. - Junde Li; Mahabubul Alam; Congzhou M. Sha; Jian Wang 094; Nikolay V. Dokholyan; Swaroop Ghosh (DAC, 2021)

Drug Discovery Approaches using Quantum Machine Learning. - Junde Li; Mahabubul Alam; Congzhou M. Sha; Jian Wang 094; Nikolay V. Dokholyan; Swaroop Ghosh (CoRR, 2021)

Predicting Protein-Ligand Docking Structure with Graph Neural Network. - Huaipan Jiang; Jian Wang 094; Weilin Cong; Yihe Huang; Morteza Ramezani; Anup Sarma; Nikolay V. Dokholyan; Mehrdad Mahdavi; Mahmut T. Kandemir (J. Chem. Inf. Model., 2022)

Yuel: Improving the Generalizability of Structure-Free Compound-Protein Interaction Prediction. - Jian Wang 094; Nikolay V. Dokholyan (J. Chem. Inf. Model., 2022)

Application of Quantum Tensor Networks for Protein Classification. - Debarshi Kundu; Archisman Ghosh; Srinivasan Ekambaram; Jian Wang 094; Nikolay V. Dokholyan; Swaroop Ghosh (ACM Great Lakes Symposium on VLSI, 2024)

Differentiable rotamer sampling with molecular force fields. - Congzhou M. Sha; Jian Wang 094; Nikolay V. Dokholyan (Briefings Bioinform., 2024)

Quantifying network behavior in the rat prefrontal cortex. - Congzhou M. Sha; Jian Wang 094; Richard B. Mailman; Yang Yang; Nikolay V. Dokholyan (Frontiers Comput. Neurosci., 2024)

Leveraging Transfer Learning for Predicting Protein-Small-Molecule Interaction Predictions. - Jian Wang 094; Nikolay V. Dokholyan (J. Chem. Inf. Model., 2025)