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Bioinformatics Vol. 17 no. 3 2001
Pages 226-236
© 2001 Oxford University Press

Original Paper

Basic Gene Grammars and DNA-ChartParser for language processing of Escherichia coli promoter DNA sequences

Siu-wai Leung , Chris Mellish and Dave Robertson

Division of Informatics, University of Edinburgh, 80 South Bridge, Edinburgh EH1 1HN, UK

Received on March 13, 2000 ; revised on October 13, 2000 ; accepted on November 21, 2000

Motivation: The field of ‘DNA linguistics’ has emerged from pioneering work in computational linguistics and molecular biology. Most formal grammars in this field are expressed using Definite Clause Grammars but these have computational limitations which must be overcome. The present study provides a new DNA parsing system, comprising a logic grammar formalism called Basic Gene Grammars and a bidirectional chart parser DNA-ChartParser.

Results: The use of Basic Gene Grammars is demonstrated in representing many formulations of the knowledge of Escherichia coli promoters, including knowledge acquired from human experts, consensus sequences, statistics (weight matrices), symbolic learning, and neural network learning. The DNA-ChartParser provides bidirectional parsing facilities for BGGs in handling overlapping categories, gap categories, approximate pattern matching, and constraints. Basic Gene Grammars and the DNA-ChartParser allowed different sources of knowledge for recognizing E.coli promoters to be combined to achieve better accuracy as assessed by parsing these DNA sequences in real-world data sets.

Availability: DNA-ChartParser runs under SICStus Prolog. It and a few examples of Basic Gene Grammars are available at the URL: http://www.dai.ed.ac.uk/~siu/DNA

Contact: {siu,chrism,dr}@dai.ed.ac.uk


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