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Article
Solving Molecular Docking Problems with Multi-Objective Metaheuristics
(MDPI, 2015)
Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. However, only a ...
Article
Multi-objective ligand-protein docking with particle swarm optimizers
(Elsevier, 2019)
In the last years, particle swarm optimizers have emerged as prominent search methods to solve the molecular docking problem. A new approach to address this problem consists in a multi-objective formulation, minimizing the ...
Article
Molecular Docking Optimization in the Context of Multi-Drug Resistant and Sensitive EGFR Mutants
(MDPI, 2016)
The human Epidermal Growth Factor (EGFR) plays an important role in signaling pathways, such as cell proliferation and migration. Mutations like G719S, L858R, T790M, G719S/T790M or T790M/L858R can alter its conformation, ...
Article
jMetalSP: A framework for dynamic multi-objective big data optimization
(Elsevier, 2018)
Multi-objective metaheuristics have become popular techniques for dealing with complex optimization problems composed of a number of conflicting functions. Nowadays, we are in the Big Data era, so metaheuristics must be ...
Article
A Study of Multiobjective Metaheuristics When Solving Parameter Scalable Problems
(IEEE Computer Society, 2010)
To evaluate the search capabilities of a multiobjective algorithm, the usual approach is to choose a benchmark of known problems, to perform a fixed number of function evaluations, and to apply a set of quality indicators. ...
Article
Inference of gene regulatory networks with multi-objective cellular genetic algorithm
(Elsevier, 2019)
Reverse engineering of biochemical networks remains an important open challenge in computational systems biology. The goal of model inference is to, based on time-series gene expression data, obtain the sparse ...