用机器学习方法估计蛋白质结构的质量:综述

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引用次数: 0

摘要

蛋白质结构预测是生物信息学中最重要和最具挑战性的问题,因为蛋白质的功能是由其结构决定的。蛋白质质量评价在蛋白质结构预测中起着重要的作用。蛋白质结构预测的目的是减少结构和序列的间隙。蛋白质结构可以用实验方法确定。实验方法非常耗时,因此我们使用机器学习方法来估计蛋白质结构,如支持向量机,隐马尔可夫模型。蛋白质结构质量的评价是成功预测蛋白质结构的关键环节之一。本文提供了关于使用机器学习方法进行蛋白质结构质量评估的详细调查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quality Estimation Of Protein Structure Using Machine Learning Approaches : A Survey
Protein structure prediction is the most important and challenging problem with bioinformatics because function of protein is determined by its structure. Protein quality assessment plays an important role in the prediction of protein structure. Aim of protein structure prediction is reducing the structure and sequence gap. Protein structure can be determined by using experimental methods. Experimental methods are very time consuming, so we use machine learning approaches to estimation of protein structure like support vector machine, hidden markov model. Assessment of the quality of protein structure is one of the key component for the successful prediction of protein structures. This article provides a detailed survey about quality assessment of protein structures using machine learning approaches.
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