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A Neural Network Model for the Prediction of Membrane-spanning Amino Acid Sequences by Reinhard Lohmann; Gisbert Schneider; Dirk Behrens; Paul Wrede is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Abstract The architecture and weights of an artificial neural network model that predicts putative transmembrane sequences have been developed and optimized by the algorithm of structure evolution. The resulting filter is able to classify membrane/nonmembrane transition regions in sequences of integral human membrane proteins with high accuracy. Similar results have been obtained for both training and test set data, indicating that the network has focused on general features of transmembrane sequences rather than specializing on the training data. Seven physicochemical amino acid properties have been used for sequence encoding. The predictions are compared to hydrophobicity plots.

Who reads A Neural Network Model for the Prediction of Membrane-spanning Amino Acid Sequences?

Author

Reinhard Lohmann; Gisbert Schneider; Dirk Behrens; Paul Wrede

Publisher

Cold Spring Harbor Laboratory Press; Wiley (John Wiley & Sons); Wiley-Blackwell; Wiley (ISSN 0961-8368)

Published

1994

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)