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Classification of Protein Interactions Based on Sparse Discriminant Analysis and Energetic Features

机译:基于稀疏判别分析和精力量特征的蛋白质相互作用分类

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Prediction of protein-protein interaction (PPI) types is an important problem in life sciences because of fundamental role of PPIs in many biological processes. In this paper we propose a new classification approach based on the extended classical Fisher linear discriminant analysis (FLDA) to predict obligate and non-obligate protein-protein interactions. To characterize properties of the protein interaction, we proposed to use the binding free energies (total of 282 features). The obtained results are better than in the previous studies.
机译:由于PPI在许多生物学过程中,PPI的基本作用是生命科学的预测是生命科学的重要问题。本文提出了一种基于扩展古典渔业线性判别分析(FLDA)的新分类方法,以预测义务和非迫使蛋白质 - 蛋白质相互作用。为了表征蛋白质相互作用的性质,我们提出使用粘合剂(总共282个特征)。获得的结果比以前的研究更好。

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