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Explore Residue Significance in Peptide Classification

机译:探讨肽分类中的残留意义

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Although peptide classification has been studied for a few decades, a proper method for studying residue significance has not yet been paid much attention. This paper introduces a novel neural learning algorithm which can be used to reveal residue significance for discriminating between functional and non-functional peptides and for peptide conformation pattern analysis. The algorithm is a revised bio-basis function neural network which was introduced a few years ago.
机译:虽然已经研究了肽分类几十年,但是研究残留物的适当方法尚未得到很多关注。本文介绍了一种新型神经学习算法,可用于揭示用于区分功能性和非功能性肽的残留意义和肽构象模式分析。该算法是几年前推出的修订生物基函数神经网络。

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