Automated biological sequence description by genetic multiobjective generalized clustering

Keyphrases

• DNA Sequencing 100%
• Biological Sequences 100%
• Multi-objective Optimization Problem 100%
• Multivariable 50%
• Genetic Algorithm 50%
• Recent Advances 50%
• Structural Features 50%
• Metabolic Pathway 50%
• Time Series Data 50%
• Evolutionary Computation 50%
• Optimization Algorithm 50%
• Optimization Objectives 50%
• Biological Knowledge 50%
• Method for Identification 50%
• Pareto Optimal Solution 50%
• Performance Criteria 50%
• Biological Macromolecules 50%
• Qualitative Features 50%
• Two-step Method 50%
• Qualitative Characteristics 50%
• Clustering Methodology 50%
• Objective Being 50%
• Specific Constraints 50%
• Fuzzy Subset 50%
• Tripanosoma Cruzi 50%

Computer Science

• Multiobjective 100%
• Biological Sequence 100%
• Optimization Problem 66%
• Optimization Algorithm 33%
• Optimisation Objective 33%
• Pareto-optimality 33%
• Performance Criterion 33%
• Time Series Data 33%
• Qualitative Characteristic 33%
• Structural Feature 33%
• Qualitative Feature 33%
• Evolutionary Computation 33%
• Information Retrieval 33%
• Genetic Algorithm 33%