posted on 2023-05-28, 01:06authored byUren, PJ, Cameron-Jones, RM, Sale, AHJ
The ability to locate promoters within a section of DNA is known to be a very difficult and very important task in DNA analysis. We document an approach that incorporates the concept of DNA as a complex molecule using several models of its physico-chemical properties. A support vector machine is trained to recognise promoters by their distinctive physical and chemical properties. We demonstrate that by combining models, we can improve upon the classification accuracy obtained with a single model. We also show that by examining how the predictive accuracy of these properties varies over the promoter, we can reduce the number of attributes needed. Finally, we apply this method to a real-world problem. The results demonstrate that such an approach has significant merit in its own right. Furthermore, they suggest better results from a planned combined approach to promoter prediction using both physicochemical and sequence based techniques.
History
Publication title
Computational Life Sciences II
Series
Lecture Notes in Bioinformatics
Number
4216
Pagination
21-31
ISBN
978-3-540-45767-1
Publisher
Springer-Verlag: Lecture Notes in Computer Science
Publication status
Published
Place of publication
Berlin; New York
Event title
The 2nd International Symposium on Computational Life Science
Event Venue
Cambridge, UK
Date of Event (Start Date)
2006-09-27
Date of Event (End Date)
2006-09-29
Rights statement
The original publication is available at www.springerlink.com