Identification of TSS in the Human Genome Based on a RBF Neural Network

被引：0
|
作者：
Zhi-Hong Peng
机构：
来源：
Machine Intelligence Research | 2006年 / 01期
基金：
中国国家自然科学基金;
关键词：
Promoter recognition; human genome; transcription start site; RBF neural network;
D O I：
暂无
中图分类号：
TP183 [人工神经网络与计算];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The identification of functional motifs in a DNA sequence is fundamentally a statistical pattern recognition problem. This paper introduces a new algorithm for the recognition of functional transcription start sites (TSSs) in human genome sequences, in which a RBF neural network is adopted, and an improved heuristic method for a 5-tuple feature viable construction, is proposed and implemented in two RBFPromoter and ImpRBFPromoter packages developed in Visual C++ 6.0. The algorithm is evaluated on several different test sequence sets. Compared with several other promoter recognition programs, this algorithm is proved to be more flexible, with stronger learning ability and higher accuracy.
引用
收藏
页码：35 / 40
页数：6
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