Parallel processing of biological sequence comparison algorithms
International Journal of Parallel Programming
Computers and Biomedical Research
A linear space algorithm for computing maximal common subsequences
Communications of the ACM
High Performance Computational Methods for Biological Sequence Analysis
High Performance Computational Methods for Biological Sequence Analysis
Parallel Simulated Annealing using Speculative Computation
IEEE Transactions on Parallel and Distributed Systems
Parallel N-ary Speculative Computation of Simulated Annealing
IEEE Transactions on Parallel and Distributed Systems
On Parallel Search of DNA Sequence Databases
Proceedings of the Fifth SIAM Conference on Parallel Processing for Scientific Computing
Parallel homologous sequence searching in large databases
FRONTIERS '95 Proceedings of the Fifth Symposium on the Frontiers of Massively Parallel Computation (Frontiers'95)
Database Allocation Strategies for Parallel BLAST Evaluation on Clusters
Distributed and Parallel Databases
Regular biosequence pattern matching with cellular automata
Information Sciences—Applications: An International Journal
Improving Performance of Multiple Sequence Alignment Analysis in Multi-Client Environments
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Proceedings of the 9th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
A component-based implementation of multiple sequence alignment
Proceedings of the 2003 ACM symposium on Applied computing
Future Generation Computer Systems - Selected papers on theoretical and computational aspects of structural dynamical systems in linear algebra and control
Journal of Parallel and Distributed Computing
Parallel evolution strategy on grids for the protein threading problem
Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing
Parallel homologous search with Hirschberg algorithm: a hybrid MPI-Pthreads solution
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
A PGAS-Based Algorithm for the Longest Common Subsequence Problem
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
Journal of Parallel and Distributed Computing
High speed biological sequence analysis with hiddenMarkov models on reconfigurable platforms
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
Efficient dominant point algorithms for the multiple longest common subsequence (MLCS) problem
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A novel approach to multiple sequence alignment using hadoop data grids
Proceedings of the 2010 Workshop on Massive Data Analytics on the Cloud
Independent component analysis algorithms for microarray data analysis
Intelligent Data Analysis - Knowledge Discovery in Bioinformatics
Parallelisation of sequence comparison algorithms using hybridised parallel techniques
HONET'09 Proceedings of the 6th international conference on High capacity optical networks and enabling technologies
Some observations on optimal frequency selection in DVFS-based energy consumption minimization
Journal of Parallel and Distributed Computing
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A massive volume of biological sequence data is available in over 36 different databases worldwide, including the sequence data generated by the Human Genome project. These databases, which also contain biological and bibliographical information, are growing at an exponential rate. Consequently, the computational demands needed to explore and analyze the data contained in these databases is quickly becoming a great concern. To meet these demands, we must use high performance computing systems, such as parallel computers and distributed networks of workstations. We present two parallel computational methods for analyzing these biological sequences. The first method is used to retrieve sequences that are homologous to a query sequence. The biological information associated with the homologous sequences found in the database may provide important clues to the structure and function of the query sequence. The second method, which helps in the prediction of the function, structure, and evolutionary history of biological sequences, is used to align a number of homologous sequences with each other. These two parallel computational methods were implemented and evaluated on an Intel iPSC/860 parallel computer. The resulting performance demonstrates that parallel computational methods can significantly reduce the computational time needed to analyze the sequences contained in large databases.