Automated protein-family classification based on hidden Markov models
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
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
Place, publisher, year, edition, pages
2015. , 23 p.
UPTEC X, 14 033
Hidden Markov model, sequence identity, cluster, automatic clustering
Bioinformatics and Systems Biology
IdentifiersURN: urn:nbn:se:uu:diva-252372OAI: oai:DiVA.org:uu-252372DiVA: diva2:810083
Molecular Biotechnology Engineering Programme
2014-05-15, 12:15 (English)
Persson, Bengt, Prof.