利用混合人工智能方法预测蛋白质结构

X. Guan, R. Mural, E. Uberbacher
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引用次数: 6

摘要

描述了一种基于人工智能方法和遗传算法预测蛋白质结构的新方法。我们将最近邻搜索算法、神经网络、启发式规则和遗传算法结合起来,形成一个集成系统,从它们的初级氨基酸序列预测蛋白质结构。首先,我们描述了我们的方法以及它们是如何集成的,然后将我们的方法应用于几个蛋白质序列。所得结果与晶体学所得的实际结构非常接近。并行遗传算法也被实现。
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Protein structure prediction using hybrid AI methods
Describes a new approach for predicting protein structures based on artificial intelligence methods and genetic algorithms. We combine nearest neighbor searching algorithms, neural networks, heuristic rules and genetic algorithms to form an integrated system to predict protein structures from their primary amino acid sequences. First, we describe our methods and how they are integrated, and then apply our methods to several protein sequences. The results are very close to the real structures obtained by crystallography. Parallel genetic algorithms are also implemented.<>
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