Buscar
Mostrando ítems 1-10 de 10
Artículo
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 ...
Artículo
A multi-objective interactive dynamic particle swarm optimizer
(Springer, 2020)
Multi-objective optimization deals with problems having two or more conflicting objectives that have to be optimized simulta-neously. When the objectives change somehow with time, the problems become dynamic, and if the ...
Artículo
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 ...
Artículo
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, ...
Artículo
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 ...
Artículo
Optimizing ligand conformations in flexible protein targets: amulti-objective strategy
(Springer, 2020)
Finding the orientation of a ligand (small molecule) with the lowest binding energy to the macromolecule (receptor) is a complex optimization problem, commonly called ligand–protein docking. This problem has been usually ...
Artículo
Qom—A New Hydrologic Prediction Model Enhanced with Multi-Objective Optimization
(MDPI, 2019)
The efficient calibration of hydrologic models allows experts to evaluate past events in river basins, as well as to describe new scenarios and predict possible future floodings. A difficulty in this context is the need ...
Artículo
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. ...
Artículo
jMetalPy: a Python Framework for Multi-Objective Optimization with Metaheuristics
(Elsevier, 2019)
This paper describes jMetalPy, an object-oriented Python-based framework for multi-objective optimization with metaheuristic techniques. Building upon our experiences with the well-known jMetal framework, we have developed ...
Artículo
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 ...