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An error tolerant software equipment for human DNA characterization

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1 Author(s)
S. Rampone ; Univ. del Sannio, Benevento, Italy

We describe a learning algorithm for the prediction of splice site locations in human DNA in the presence of sequence annotation errors in the training data. Experimental results on a common dataset including errors are reported. We also give an efficient implementation. The resulting software package is publicly available.

Published in:

IEEE Transactions on Nuclear Science  (Volume:51 ,  Issue: 5 )