Enhancement of proclust algorithm using parallel methods for protein sequence clustering
| dc.contributor.author | Haj Assayony, Mohammed Omer | |
| dc.date.accessioned | 2015-07-30T05:39:48Z | |
| dc.date.available | 2015-07-30T05:39:48Z | |
| dc.date.issued | 2008 | |
| dc.description.abstract | Graph-based protein sequences clustering algorithms produce good results in clustering protein sequences into accurate cluster. The main advantage of these algorithms is that they convert the clustering problem into a well-known problem in graph theory and use the algorithms and techniques used in graph theory to deal with it. The drawback of these algorithms is that they exploit long time in producing the results. This research is about studying these algorithms and designing parallel methods and techniques to improve the performance of these algorithms. The research concentrates on designing parallel methods for improving the performance of one of these algorithms: ProClust which is depending on the concept of finding strongly connected components of a directed graph. The methods and techniques that we have designed for improving ProClust are suggested to be vsed in other graph-based protein sequence clustering. The suggested parallel methods distribute the computational work of the algorithm almost evenly among a set of interconnected processors such that the communications among them are low comparing with the computational load. The results of implementing the parallel method used in improving the main step in ProClust, which is the process of finding strongly connected components of the directed graph, are acceptable comparing with the results obtained from other works. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/1063 | |
| dc.language.iso | en | en_US |
| dc.subject | Proclust algorithm | en_US |
| dc.subject | Sequence clustering | en_US |
| dc.title | Enhancement of proclust algorithm using parallel methods for protein sequence clustering | en_US |
| dc.type | Thesis | en_US |
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