Integrating Genomic Homology into Gene Structure Prediction

Integrating Genomic Homology into Gene Structure Prediction (2001)

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by Ian Korf , Paul Flicek , Daniel Duan , Michael R. Brent

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Datum	Value	Source
TITLE	Integrating Genomic Homology into Gene Structure Prediction	user correction - Legacy Corrections
AUTHOR NAME	Ian Korf	user correction - Legacy Corrections
AUTHOR AFFIL	1 Department of Computer Science, Washington University	user correction - Legacy Corrections
AUTHOR ADDR	Campus Box 1045, St.	user correction - Legacy Corrections
AUTHOR NAME	Paul Flicek	user correction - Legacy Corrections
AUTHOR NAME	Daniel Duan	user correction - Legacy Corrections
AUTHOR NAME	Michael R. Brent	user correction - Legacy Corrections
AUTHOR AFFIL	University, Campus Box 1097, St. Louis	user correction - Legacy Corrections
AUTHOR ADDR	MO, 63130, USA	user correction - Legacy Corrections
ABSTRACT	TWINSCAN is a new gene-structure prediction system that directly extends the probability model of GENSCAN, allowing it to exploit homology between two related genomes. Separate probability models are used for conservation in exons, introns, splice sites, and UTRs, reflecting the differences among their patterns of evolutionary conservation. TWINSCAN is specifically designed for the analysis of high-throughput genomic sequences containing an unknown number of genes. In experiments on high-throughput mouse sequences, using homologous sequences from the human genome, TWINSCAN shows notable improvement over GENSCAN in exon sensitivity and specificity and dramatic improvement in exact gene sensitivity and specificity. This improvement can be attributed entirely to modeling the patterns of evolutionary conservation in genomic sequence.	SVM HeaderParse 0.1
YEAR	2001	user correction - Legacy Corrections
CITATIONS	24 found	ParsCit 1.0