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Heuristic multi-sequence search methods
University of Skövde, Department of Computer Science.
2001 (English)Independent thesis Basic level (degree of Bachelor)Student thesis
Abstract [en]

With increasing size of sequence databases heuristic search approaches have become necessary. Hidden Markov models are the best performing search methods known today with respect to discriminative power, but are too time complex to be practical when searching in large sequence databases. In this report, heuristic algorithms that reduce the search space before searching with traditional search algorithms of hidden Markov models are presented and experimentally validated. The results of the validation show that the heuristic search algorithms will speed up the searches without decreasing their discriminative power.

Place, publisher, year, edition, pages
Skövde: Institutionen för datavetenskap , 2001. , 58 p.
Keyword [en]
Heuristic multi-sequence search methods
National Category
Computer Science
Identifiers
URN: urn:nbn:se:his:diva-530OAI: oai:DiVA.org:his-530DiVA: diva2:2913
Uppsok
teknik
Supervisors
Available from: 2008-01-18 Created: 2008-01-18

Open Access in DiVA

fulltext(997 kB)193 downloads
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File name FULLTEXT01.psFile size 997 kBChecksum MD5
fd38788a2ade0eccd5c26261b04b57c70b54abccd78b5772cd9f07e3dd3f28ce6b4d4ebf
Type fulltextMimetype application/postscript

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf