Autors: Ivanova, D. A., Tsvetanov, S. E., Boris Zografov.
Title: Ant Colony Optimization Applied for Multiple Sequence Alignment
Keywords: Ant Colony Optimization, Multiple Sequence Alignment

Abstract: The paper presents Multiple Sequence Alignment (MSA) as a computation problem and proposes Ant Colony Optimization (ACO) based solution. The MSA is widely applied in the area of bioinformatics and has high compute complexity, which is hard for solving, especially for huge data sets. Ant Colony Optimization (ACO) is metaheuristic method applied for solving different kind of combinatorial problems. The main idea of the developed program implementation for solving MSA as follow: The ant takes a sequence and moves in the area associated with each sequence, increasing the pheromone level when finds similarity in the position. Dynamic program analysis using Scalasca tool has been performed to define the bottlenecks in the code and the problematic areas has been optimized for parallel computation. The experimental results shows that the developed program could be successfully used for solving MSA problem.

References

    Issue

    Biomath, 2015, Bulgaria, Biomath, http://dx.doi.org/10.11145/496

    Copyright Biomath

    Цитирания (Citation/s):
    1. Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm - 2016 - в издания, индексирани в Scopus или Web of Science
    2. Bacterial foraging optimization–genetic algorithm for multiple sequence alignment with multi-objectives - 2017 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
    3. Influence of Parameters in Multiple Sequence Alignment Methods for Protein Sequences - 2018 - в издания, индексирани в Scopus или Web of Science
    4. A Novel Multiple Sequence Alignment Algorithm Based on Artificial Bee Colony and Particle Swarm Optimization - 2019 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, индексирана в Web of Science