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Bio-inspired optimization for the molecular docking problem: State of the art, recent results and perspectives.

, , , , , and . Appl. Soft Comput., (2019)

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Bio-inspired optimization for the molecular docking problem: State of the art, recent results and perspectives., , , , , and . Appl. Soft Comput., (2019)jMetalCpp: optimizing molecular docking problems with a C++ metaheuristic framework., , , and . Bioinform., 30 (3): 437-438 (2014)Multi-objective ligand-protein docking with particle swarm optimizers., , , , and . Swarm Evol. Comput., (2019)Optimizing ligand conformations in flexible protein targets: a multi-objective strategy., , , , and . Soft Comput., 24 (14): 10705-10719 (2020)Sharing and executing linked data queries in a collaborative environment., , , and . Bioinform., 29 (13): 1663-1670 (2013)VIGLA-M: visual gene expression data analytics., , , , , , and . BMC Bioinform., 20-S (4): 150:1-150:11 (2019)Solving molecular flexible docking problems with metaheuristics: A comparative study., , , , and . Appl. Soft Comput., (2015)A Study of Archiving Strategies in Multi-objective PSO for Molecular Docking., , , , , and . ANTS Conference, volume 9882 of Lecture Notes in Computer Science, page 40-52. Springer, (2016)A New Multi-objective Approach for Molecular Docking Based on RMSD and Binding Energy., , , , and . AlCoB, volume 9702 of Lecture Notes in Computer Science, page 65-77. Springer, (2016)Multi-objective Metaheuristics for a Flexible Ligand-Macromolecule Docking Problem in Computational Biology., , , , and . IDC, volume 798 of Studies in Computational Intelligence, page 369-379. Springer, (2018)