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Automated protein-family classification based on hidden Markov models
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Bioinformatik.
2015 (engelsk)Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
Abstract [en]

The aim of the project presented in this paper was to investigate the possibility toautomatically sub-classify the superfamily of Short-chain Dehydrogenase/Reductases (SDR).This was done based on an algorithm previously designed to sub-classify the superfamily ofMedium-chain Dehydrogenase/Reductases (MDR). While the SDR-family is interesting andimportant to sub-classify there was also a focus on making the process as automatic aspossible so that future families also can be classified using the same methods.To validate the results generated it was compared to previous sub-classifications done on theSDR-family. The results proved promising and the work conducted here can be seen as a goodinitial part of a more comprehensive full investigation

sted, utgiver, år, opplag, sider
2015. , s. 23
Serie
UPTEC X ; 14 033
Emneord [en]
Hidden Markov model, sequence identity, cluster, automatic clustering
HSV kategori
Identifikatorer
URN: urn:nbn:se:uu:diva-252372OAI: oai:DiVA.org:uu-252372DiVA, id: diva2:810083
Utdanningsprogram
Molecular Biotechnology Engineering Programme
Presentation
2014-05-15, 12:15 (engelsk)
Veileder
Examiner
Tilgjengelig fra: 2015-05-06 Laget: 2015-05-06 Sist oppdatert: 2016-05-05bibliografisk kontrollert

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