Title :
Ab initio exon definition using an information theory-based approach
Author_Institution :
Univ. of Western Ontario, London, ON
Abstract :
Transcribed exons in genes are joined together at donor and acceptor splice sites precisely and efficiently to generate mRNAs capable 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.
Keywords :
Monte Carlo methods; bioinformatics; information theory; macromolecules; organic compounds; Ab initio exon definition; Shannon information theory; biological mechanisms; information theory-based approach; mRNA; Bioinformatics; Entropy; Genetic communication; Humans; Information theory; Proteins; RNA; Sensitivity and specificity; Thermodynamics; Upper bound; Biological System Modeling; Genetics; Information Theory; Monte Carlo Methods;
Conference_Titel :
Information Sciences and Systems, 2009. CISS 2009. 43rd Annual Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-2733-8
Electronic_ISBN :
978-1-4244-2734-5
DOI :
10.1109/CISS.2009.5054835