Parallel Compressed-Domain Pattern Matching Algorithms With Burrows Wheeler Transform For Biological Data

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dc.contributor.authorUmar, Ibrahim
dc.date.accessioned2018-06-12T06:35:42Z
dc.date.available2018-06-12T06:35:42Z
dc.date.issued2010-05
dc.description.abstractData compression is one of the solution to overcome data storage problem. Unfortunately, compression may have removed a great deal of information structure that will make searching s desired piece of data difficult. Burrows-Wheeler Transform (BWT) compression offers a very effective compression ratio and a pomising potential in terms of text searching because of its close relationship with text index. We proposed two efficient parallel text searching algorithms and a compact compressed data representation for biological data derived from BWT named Compressed Semi-self Index (cSSI).en_US
dc.identifier.urihttp://hdl.handle.net/123456789/5738
dc.language.isoenen_US
dc.publisherUniversiti Sains Malaysiaen_US
dc.subjectData compression is one of the solutionen_US
dc.subjectto overcome data storage problemen_US
dc.titleParallel Compressed-Domain Pattern Matching Algorithms With Burrows Wheeler Transform For Biological Dataen_US
dc.typeThesisen_US
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