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首页> 外文会议>Iranian Conference on Biomedical Engineering >Protein complex identification by graph local clustering and use of Chou's amphiphilic Pseudo amino-acid features
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Protein complex identification by graph local clustering and use of Chou's amphiphilic Pseudo amino-acid features

机译：蛋白质复杂鉴定通过图局部聚类和使用Chou's Amphiphic伪氨基酸特征

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The intend of this paper is to introduce a new method for protein complex identification. Proteins share an important role by signaling cells. Proteins are three dimensional objects and any types of deformed proteins can cause severe disease, because their function is related to their shape and also the amino-acid sequence they have coded with. Technically speaking similar types of proteins tend to act by forming a group or a complex and if we can find a highly accurate way to identify the complexes we can find a group of proteins that are responsible for something. For this purpose different types of algorithms have proposed but most of them failed to achieve enough precision. Here we will use a new method which uses Chou Pseudo amino-acid as a set of features and we will get a good result even by using machine learning techniques that were supposed as not an effective tool in this field before.
机译：本文的意图是为蛋白质复杂鉴定引入一种新方法。蛋白质通过信号传导细胞分享重要作用。蛋白质是三维物体，并且任何类型的变形蛋白质都会导致严重疾病，因为它们的功能与它们的形状有关，并且它们已经编码了它们的形状。在技​​术上，讲的类似类型的蛋白质倾向于通过形成组或复杂，并且如果我们能够找到识别复合物的高准确方式，我们可以找到一组负责某事的蛋白质。为此目的，提出了不同类型的算法，但大多数未能达到足够的精度。在这里，我们将使用一种新方法，该方法使用Chou伪氨基酸作为一组功能，甚至通过使用之前在该领域中没有有效工具的机器学习技术，我们将获得良好的结果。

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