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Application of expert networks for predicting proteins secondary structure

Paper ID Volume ID Publish Year Pages File Format Full-Text
14097 1147 2007 7 PDF Available
Title
Application of expert networks for predicting proteins secondary structure
Abstract

The present study utilizes expert neural networks for the prediction of proteins secondary structure. We use three independent networks, one for each structure (alpha, beta and coil) as the first-level processing unit; decision upon the chosen structure for each residue is carried out by a second-level, post-processing unit, which utilizes the Chou and Fasman frequency values Fα and Fβ in order to strengthen and/or deplete the probability of the specific structure under investigation. The highest prediction case was 76%.Our method requires primitive computational means and a relatively small training set, while still been comparable to previous work. It is not meant to be an alternative to the determination of secondary structure by means of free energy minimization, integration of dynamic equations of motion or crystallography, which are expensive, time-consuming and complicated, but to provide additional constrains, which might be considered and incorporated into larger computing setups in order to reduce the initial search space for the above methods.

Keywords
Proteins; Secondary structure prediction; Expert neural networks; Chou and Fasman frequency parameters
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biomolecular Engineering - Volume 24, Issue 2, June 2007, Pages 237–243
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us