Facilitates the visualization of conformations through two clustering methods. The first method is K-RMSD, which is based on the clustering through (RMSD) and enables the interactive visualization of groups through a treemap, and the other one is based on the hierarchical clustering called AGNES. Using an algorithm of average distances generates a dendogram that offers the possibility to explore sequentially the groups that illustrate best the docking. The fact that both visualizations are connected to PyMOL increases its ability of discernment.

How to cite:

Varela-Salinas, Génesis; García-Pérez, C. A.; Peláez, R. & Rodríguez, A. J. Visual Clustering Approach for Docking Results from Vina and AutoDock, Hybrid Artificial Intelligent Systems: 12th International Conference, HAIS 2017, La Rioja, Spain, June 21-23, 2017, Proceedings, Springer International Publishing, 2017, 342-353

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