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A Cloud-Based Workflow Approach for Optimizing Molecular Docking Simulations of Fully-Flexible Receptor Models and Multiple Ligands.

, , and . CloudCom, page 495-498. IEEE Computer Society, (2015)

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Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments., , , , and . Comput. Intell. Neurosci., (2015)SmartIX: A database indexing agent based on reinforcement learning., , , , , and . Appl. Intell., 50 (8): 2575-2588 (2020)Clustering Molecular Dynamics Trajectories with a univariate estimation of distribution algorithm., , , and . CEC, page 2058-2065. IEEE, (2015)eXplainable Artificial Intelligence on Medical Images: A Survey., , , , , , , , , and 8 other author(s). CoRR, (2023)Efficient Brazilian Sign Language Recognition: A Study on Mobile Devices., , , , , , , and . CIARP, volume 14469 of Lecture Notes in Computer Science, page 406-419. Springer, (2023)A Cloud-Based Workflow Approach for Optimizing Molecular Docking Simulations of Fully-Flexible Receptor Models and Multiple Ligands., , and . CloudCom, page 495-498. IEEE Computer Society, (2015)An effective method to optimize docking-based virtual screening in a clustered fully-flexible receptor model deployed on cloud platforms.. Pontifícia Universidade Católica do Rio Grande do Sul, Brazil, (2016)ndltd.org (oai:tede2.pucrs.br:tede/7329).A strategic solution to optimize molecular docking simulations using Fully-Flexible Receptor models., , , and . Expert Syst. Appl., 41 (16): 7608-7620 (2014)A Conceptual Many Tasks Computing Architecture to Execute Molecular Docking Simulations of a Fully-Flexible Receptor Model., , , and . BSB, volume 6832 of Lecture Notes in Computer Science, page 75-78. Springer, (2011)A selective method for optimizing ensemble docking-based experiments on an InhA Fully-Flexible receptor model., , , , and . BMC Bioinform., 19 (1): 235:1-235:16 (2018)