DocumentCode
2118045
Title
Prediction of Selenoproteins Based on Motif Recognition
Author
Tao, Lan ; Liu, Geng ; Wang, Xiaoli ; Zhang, Lei
Author_Institution
Coll. of Comput. & Software, Shenzhen Univ., Shenzhen, China
fYear
2009
fDate
17-19 Oct. 2009
Firstpage
1
Lastpage
5
Abstract
At present available computational methods can not predict selenoproteins correctly because of the special features of selenoproteins. It is known that there are some conservative sections around U in selenoproteins from previous research. So we bring forward a new method to predict selenoproteins based on motif recognition, we use Multiple Em for Motif Elicitation (MEME) to discover motif around U in selenoproteins and then predict selenoproteins based on the motif. The new method found all the selenoproteins in 9 seleno families expect one false positive in family of GPX1 and one in SelS. From the experiment, it is showed that this method can effectively predict almost all the selenoproteins in the known seleno families, and better than the methods of locating the position of U and blasting the Sec/Cys pairing based on handcraft.
Keywords
proteins; proteomics; GPX1 family; Multiple Em for Motif Elicitation; motif recognition; selenoproteins prediction; Amino acids; Educational institutions; Humans; Learning systems; Organisms; Predictive models; Proteins; Pulse width modulation; Sequences; Software;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on
Conference_Location
Tianjin
Print_ISBN
978-1-4244-4132-7
Electronic_ISBN
978-1-4244-4134-1
Type
conf
DOI
10.1109/BMEI.2009.5302720
Filename
5302720
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