DocumentCode
480630
Title
UKF Based Self-Organizing Feature Maps Algorithm for the Recognition of Splice Sites
Author
Su, Hongquan ; Zhu, Yi-Shen ; Zhang, Xiao-Hui
Author_Institution
Inf. Coll., Dalian Maritime Univ., Dalian
Volume
2
fYear
2008
fDate
20-22 Dec. 2008
Firstpage
543
Lastpage
547
Abstract
Due to the higher dimensional and nonlinear properties of the gene sequences, traditional self-organizing feature maps can´t identify splice sites effectively. To circumvent the parameters study of the self-organizing feature maps, a method is presented based on the Kalman filter and the unscented transform which can identify splice sites effectively. By identifying the splice sites form long-scale and short-scale genomic DNA sequences, results show that the novel algorithm has competence.
Keywords
DNA; Kalman filters; biology computing; genomics; self-organising feature maps; Kalman filter; UKF based self-organizing feature maps algorithm; gene sequences; genomic DNA sequences; splice sites recognition; unscented transform; Bioinformatics; DNA; Educational institutions; Filters; Genomics; Information technology; Jacobian matrices; Nearest neighbor searches; Neurons; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
Conference_Location
Shanghai
Print_ISBN
978-0-7695-3497-8
Type
conf
DOI
10.1109/IITA.2008.367
Filename
4739823
Link To Document