Abstract
Motivation: Our aim is to utilize an artificial neural network (ANN) for the prediction of DNA curvature in terms of retardation anomaly. Results: An ANN capturing the role of phasing, increased helix flexibility, run of poly(A) tracts and flanking base pair effects in determining the extent of DNA curvature has been developed. The network predictions validate the known experimental results and also explain how the base pairs other than ApA affect the curvature. Availability: The optimal weights and the procedure to compute the retardation anomaly value are available on request from the authors. Contact: bdk@@@ems.ncl.res.in.
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CITATION STYLE
Parbhane, R. V., Tambe, S. S., & Kulkarni, B. D. (1998). Analysis of DNA curvature using artificial neural networks. Bioinformatics, 14(2), 131–138. https://doi.org/10.1093/bioinformatics/14.2.131
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