DocumentCode
3355338
Title
Prediction of Transmembrane Helical Segments in Membrane Proteins Using Back Propagation Neural Network with Wavelet Analysis
Author
Yu Bin
Author_Institution
Coll. of Math. & Phys., Qingdao Univ. of Sci. & Technol., Qingdao, China
Volume
2
fYear
2009
fDate
28-30 Oct. 2009
Firstpage
563
Lastpage
567
Abstract
Transmembrane proteins possess important physiological function. The increasing transmembrane protein sequences from genome projects raise the needs for theoretical methods to predict their structures, especially transmembrane helical segments (TMHs). wnnTM, a new method of BP neural network based on wavelet multiresolution analysis (MRA) is initially developed to predict the number and location of TMHs in membrane proteins. 80 proteins with known 3D-structure randomly selected from Mptopo database are used as test set to evaluate the prediction accuracy of the method. The final results indicate that the proposed method is more effective than BP neural network model only.
Keywords
backpropagation; bioinformatics; biomembranes; neural nets; proteins; Mptopo database; backpropagation neural network; genome sequences; transmembrane helical segments prediction; transmembrane protein sequences; wavelet multiresolution analysis; Accuracy; Bioinformatics; Biomembranes; Databases; Genomics; Multiresolution analysis; Neural networks; Protein engineering; Testing; Wavelet analysis; BP neural network; membrane protein; transmembrane helical segments; wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Engineering, 2009. WCSE '09. Second International Workshop on
Conference_Location
Qingdao
Print_ISBN
978-0-7695-3881-5
Type
conf
DOI
10.1109/WCSE.2009.876
Filename
5403518
Link To Document