A multilayer perceptron feature extractor for reading sequenced DNA autoradiograms

Author

Murdock, Michael C. ; Cotter, Neil E. ; Gesteland, Raymond

Author_Institution

Adv. Artificial Intelligence Lab., Motorola Gov. Electron. Group, Scottsdale, AZ, USA

fYear

1991

fDate

30 Sep-1 Oct 1991

Firstpage

562

Lastpage

569

Abstract

The authors report on the application of the three-layer, backward error propagation neural network to the problem of reading sequenced DNA autoradiograms. The network is used for band identification by extracting two features: band intensity level and band intensity gradient. A training set of 16000 12×12 gray scale patterns is generated. Trained with these patterns, the network successfully learned to identify the degree of presence and absence of these two low level features

Keywords

DNA; backpropagation; biological techniques and instruments; feature extraction; image processing; learning (artificial intelligence); neural nets; radioisotope scanning and imaging; backward error propagation neural network; band intensity gradient; gray scale patterns; multilayer perceptron feature extractor; sequenced DNA autoradiograms; three-layer network; Biomedical imaging; Cities and towns; DNA; Data mining; Feature extraction; Humans; Multilayer perceptrons; Neural networks; Sequences; Visual system;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop

Conference_Location

Princeton, NJ

Print_ISBN

0-7803-0118-8

Type

conf

DOI

10.1109/NNSP.1991.239485

Filename

239485