Data for Identifying Knot Types of Polymer Conformations by Machine Learning

Training Data and Generalizability Testsets For the publication PhysRevE.101.022502 @article{PhysRevE.101.022502, title = {Identifying knot types of polymer conformations by machine learning}, author = {Vandans, Olafs and Yang, Kaiyuan and Wu, Zhongtao and Dai, Liang}, journal = {Phys. Rev. E}, volume = {101}, issue = {2}, pages = {022502}, numpages = {10}, year = {2020}, month = {Feb}, publisher = {American Physical Society}, doi = {10.1103/PhysRevE.101.022502}, url = {https://link.aps.org/doi/10.1103/PhysRevE.101.022502} } GitHub source code demo using this dataset: 🥨 https://github.com/CompSoftMatterBiophysics-CityU-HK/Identify-Knot-Types-by-ML-PRE2020 The above GitHub repo provide a docker, training code, best model with weights, and two showcases of generalizability.