Ab initio exon definition using an information theory-based approach

被引:1
|
作者
Rogan, Peter K. [1 ]
机构
[1] Schulich Sch Med & Dent, London, ON N6A 5C1, Canada
关键词
Biological System Modeling; Genetics; Information Theory; Monte Carlo Methods; PRE-MESSENGER-RNA; U1; SNRNA; GENE; RECOGNITION; SEQUENCES; MUTATIONS; YEAST; U2;
D O I
10.1109/CISS.2009.5054835
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Transcribed exons in genes are joined together at donor and acceptor splice sites precisely and efficiently to generate mRNAs capa(1)ble of being translated into proteins. The sequence variability in individual splice sites can be modeled using Shannon information theory. In the laboratory, the degree of individual splice site use is inferred from the structures of mRNAs and their relative abundance. These structures can be predicted using a bipartite information theory framework that is guided by current knowledge of biological mechanisms for exon recognition. We present the results of this analysis for the complete dataset of all expressed human exons.
引用
收藏
页码:847 / 852
页数:6
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