Name
Abstract | ||
|---|---|---|
In silico biological sequence processing is a key for molecular biology. This scientific area requires powerful computing resources for exploring large sets of biological data. Multiple sequence alignment is widely used method for biological sequence processing. The goal of this method is DNA and protein sequences alignment. This paper presents an innovative parallel algorithm MSA_BG for multiple alignment of biological sequences that is highly scalable and locality aware. The designed MSA_BG algorithm is iterative and is based on the concept of Artificial Bee Colony metaheuristics and the concept of algorithmic and architectural spaces correlation. The metaphor of the ABC metaheuristics has been constructed and the functionalities of the agents have been defined. The conceptual parallel model of computation has been designed. The algorithmic framework of the designed parallel algorithm has been constructed. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TSP.2013.6614014 | 2013 36TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP) |
Keywords | Field | DocType |
Artificial Bee Colony, Bioinformatics, High Performance Computing, Multiple sequence Alignment | Biological data,Locality,Computer science,Parallel algorithm,Massively parallel,Algorithm,Theoretical computer science,Model of computation,Multiple sequence alignment,Scalability,Metaheuristic | Conference |
Citations | PageRank | References |
1 | 0.38 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Plamenka Borovska | 1 | 15 | 7.05 |
| Veska Gancheva | 2 | 4 | 3.57 |
| Nikolay Landzhev | 3 | 1 | 0.38 |