Bioinformatics, Vol 14, 131-138, Copyright © 1998 by Oxford University Press
RV Parbhane, SS Tambe and BD Kulkarni
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. The results suggest that ANN can be used as a
model-free tool for studying DNA 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
ARTICLES
Analysis of DNA curvature using artificial neural networks
Chemical Engineering Division, National Chemical Laboratory, Pune, India.
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