DocumentCode :
1921836
Title :
Classification of eukaryotic and prokaryotic cells by a backpropagation network
Author :
Kristensen, Terje ; Patel, Ruben
Author_Institution :
Dept. of Comput. Sci., Bergen Univ. Coll., Norway
Volume :
3
fYear :
2003
fDate :
20-24 July 2003
Firstpage :
1718
Abstract :
In this paper we show how a Backpropagation neural network is used to classify between eukaryotic and prokaryotic cells. The classification is based on their DNA (Deoxyribonuclei) sequences which are obtained from different databases available on the Internet. The sequences are first preprocessed using a sliding window technique to obtain sub-sequence frequencies, and then normalised to make them comparable.
Keywords :
DNA; backpropagation; biology computing; molecular biophysics; neural nets; DNA sequence; backpropagation neural network; cell classification; deoxyribonucleic acid; eukaryotic cell; prokaryotic cell; sliding window technique; subsequence frequencies; Backpropagation; Bioinformatics; Biology computing; DNA; Frequency; Genomics; Humans; Neural networks; Neurons; Sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN :
1098-7576
Print_ISBN :
0-7803-7898-9
Type :
conf
DOI :
10.1109/IJCNN.2003.1223666
Filename :
1223666
Link To Document :
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