Section 52
Chapter 51,281

A two-stage neural network based technique for protein secondary structure prediction

Kakumani, R.; Devabhaktuni, V.; Ahmad, M.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2008: 1355-1358


ISSN/ISBN: 2375-7477
PMID: 19162919
DOI: 10.1109/iembs.2008.4649416
Accession: 051280882

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Protein secondary structure prediction is one of the most important research areas in bioinformatics. In this paper, we propose a two-stage protein secondary structure prediction technique, implemented using neural network models. The first neural network stage of the proposed technique associates the input protein sequence to a bin containing its corresponding homologues. The second stage predicts the secondary structure of the input sequence utilizing a neural prediction model specific to the bin obtained from stage one. The strategy of binning allows for simplified and accurate neural models. This technique is implemented on the RS126 dataset and its prediction accuracy is compared with that of the standard PHD approach.

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