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Neural network predicts sequence of TP53 gene based on DNA chip.
- Source :
-
Bioinformatics (Oxford, England) [Bioinformatics] 2002 Aug; Vol. 18 (8), pp. 1133-4. - Publication Year :
- 2002
-
Abstract
- Unlabelled: 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.<br />Availability: The trained neural network is available for academic use by contacting steen@cbs.dtu.dk
- Subjects :
- Base Sequence
Humans
Molecular Sequence Data
Predictive Value of Tests
Reproducibility of Results
Sensitivity and Specificity
Genes, p53 genetics
In Situ Hybridization, Fluorescence methods
Neural Networks, Computer
Oligonucleotide Array Sequence Analysis methods
Sequence Analysis, DNA methods
Subjects
Details
- Language :
- English
- ISSN :
- 1367-4803
- Volume :
- 18
- Issue :
- 8
- Database :
- MEDLINE
- Journal :
- Bioinformatics (Oxford, England)
- Publication Type :
- Academic Journal
- Accession number :
- 12176837
- Full Text :
- https://doi.org/10.1093/bioinformatics/18.8.1133