Recognition of gene acceptor site based on multi-objective optimization.
A new method for predicting the gene acceptor site based on multi-objective optimization is introduced in this paper. The models for the acceptor, branch and distance between acceptor site and branch site were constructed according to the characteristics of the sequences from the exon-intron database and using common biological knowledge. The acceptor function, branch function and distance function were defined respectively, and the multi-objective optimization model was constructed to recognize the splice site. The test results show that the algorithm used in this study performs better than the SplicePredictor, which is one of the leading acceptor site detectors.
School of Life Science and Technology, Shanghai Jiaotong University, Shanghai 200240, China.
Jing
J
Zhao
Yue-Min
YM
Zhu
Pei-Ming
PM
Song
Qing
Q
Fang
Jian-Hua
JH
Luo
D000465:Algorithms; D019295:Computational Biology; D005091:Exons; D007438:Introns; D008957:Models, Genetic; D022821:RNA Splice Sites / Q000235:genetics*; D012326:RNA Splicing / Q000502:physiology*; D017421:Sequence Analysis
D022821:RNA Splice Sites