Artificial Intelligence in Prediction of Secondary Protein Structure Using CB513 Database.

Zikrija Avdagic, Elvir Purisevic, Samir Omanovic, Zlatan Coralic
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Abstract

In this paper we describe CB513 a non-redundant dataset, suitable for development of algorithms for prediction of secondary protein structure. A program was made in Borland Delphi for transforming data from our dataset to make it suitable for learning of neural network for prediction of secondary protein structure implemented in MATLAB Neural-Network Toolbox. Learning (training and testing) of neural network is researched with different sizes of windows, different number of neurons in the hidden layer and different number of training epochs, while using dataset CB513.

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Abstract Image

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基于CB513数据库的人工智能蛋白质二级结构预测。
在本文中,我们描述了CB513一个非冗余数据集,适合开发用于预测二级蛋白质结构的算法。在Borland Delphi中编写了一个程序,对我们的数据集进行数据转换,使其适合神经网络的学习,并在MATLAB neural - network Toolbox中实现对二级蛋白质结构的预测。以CB513为数据集,研究了不同窗口大小、不同隐层神经元个数和不同训练epoch数下神经网络的学习(训练和测试)问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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