Title
High Performance System Framework for Parallel in-Silico Biological Simulations
Abstract
The parallel implementation of methods and algorithms for analysis of biological data using high-performance computing is essential for accelerating the research and reduce the investment. The paper presents a high-performance framework for carrying out scientific experiments in the area of bioinformatics, on the basis of parallel computer simulations on a heterogeneous compact computer cluster. Several of the most popular and widely used methods and algorithms using for simulations intended for high performance platforms in order to increase the efficiency of the computations have been implemented. Important role is building up a database consisting of a reference genetic biological data, advanced software tools for in-silico simulations for the purposes of molecular biology, and web portal enabling secure access to the services. Web portal provides as services access and extraction of biological data and execution of various parallel program implementations based on algorithms for comparative analysis of biological data. The proposed framework is verified experimentally for the case study of investigation the influenza virus variability.
Year
DOI
Venue
2011
10.1109/DeSE.2011.72
DeSE
Keywords
Field
DocType
reference genetic biological data,heterogeneous compact computer cluster,parallel implementation,high-performance framework,high-performance computing,biological data,web portal,parallel in-silico biological simulations,high performance system framework,comparative analysis,various parallel program,parallel computer simulation,bioinformatics,molecular biophysics,databases,parallel computer,genetics,molecular biology,parallel programming,genomics,high performance computing
Biological data,System framework,Supercomputer,Computer science,Implementation,Computational science,Software,Computer cluster,In silico,Computation,Distributed computing
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Plamenka Borovska1157.05
Ognian Nakov211.73
Veska Gancheva343.57
Ivailo Georgiev400.68