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Detection and analysis of megasatellites in the human genome using in silico methods

Megasatellites are polymorphic tandem repetitive sequences with repeat-units longer than or equal to 1000 base pairs. The novel algorithm Megasatfinder predicts megasatellites in the human genome. A structured method of analysing the algorithm is developed and conducted. The analysis method consists of six test scenarios. Scripts are created, which execute the algorithm using various parameter settings. Three nucleotide sequences are applied; a real sequence extracted from the human genome and two random sequences, generated using different base probabilities. Usability and accuracy are investigated, providing the user with confidence in the algorithm and its output. The results indicate that Megasatfinder is an excellent tool for the detection of megasatellites and that the generated results are highly reliable. The results of the complete analysis suggest alterations in the default parameter settings, presented as user guidelines, and state that artificially generated sequences are not applicable as models for real DNA in computational simulations.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-961
Date January 2005
CreatorsBenediktsson, Elís Ingi
PublisherHögskolan i Skövde, Institutionen för kommunikation och information, Skövde : Institutionen för kommunikation och information
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/postscript, application/pdf
Rightsinfo:eu-repo/semantics/openAccess, info:eu-repo/semantics/openAccess

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