Multiple Sequence Alignment Using SAGA: Investigating the Effects of Operator Scheduling, Population Seeding, and Crossover Operators.
René ThomsenWouter BoomsmaPublished in: EvoWorkshops (2004)
Keyphrases
- multiple sequence alignment
- selection operator
- crossover operator
- genetic algorithm
- mutation operator
- evolutionary algorithm
- population diversity
- differential evolution
- memory efficient
- multi objective
- protein sequences
- genetic algorithm ga
- fitness function
- traveling salesman problem
- hard constraints
- computational biology
- scheduling problem
- secondary structure
- biological sequences
- simulated annealing
- mutation probability
- multiple alignment
- sequence alignment
- optimization algorithm
- pairwise
- convergence rate
- search heuristics
- artificial neural networks
- tabu search
- neural network