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Bioinformatics Vol. 18 no. 8 2002
Pages 1133-1134
© 2002 Oxford University Press

Applications Note

Neural network predicts sequence of TP53 gene based on DNA chip

Jeppe S. Spicker 1, Friedrik Wikman 2, Ming-Lan Lu 3, Carlos Cordon-Cardo 3, Christopher Workman 1, Torben F. Ørntoft 2, Søren Brunak 1 and Steen Knudsen 1,*

1 Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark
2 Molecular Diagnostic Laboratory, Department of Clinical Biochemistry, Aarhus University Hospital, 8200 Aarhus N, Denmark
3 Department of Pathology, Memorial Sloan–Kettering Cancer Center, 1275 York Ave, New York, NY 10021, USA

Received on November 23, 2002 ; revised on February 21, 2002 ; accepted on February 28, 2002

Summary: We have trained an artificial neural network to predict the sequence of the human TP53 tumor suppressor gene based on a p53 GeneChip. The trained neural network uses as input the fluorescence intensities of DNA hybridized to oligonucleotides on the surface of the chip and makes between zero and four errors in the predicted 1300 bp sequence when tested on wild-type TP53 sequence.

Availability: The trained neural network is available for academic use by contacting steen{at}cbs.dtu.dk

Contact: steen{at}cbs.dtu.dk

* To whom correspondence should be addressed.


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