Predicting Protein-Protein Interactions with K-Nearest Neighbors Classification Algorithm

机译：用K最近邻分类算法预测蛋白质与蛋白质的相互作用

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In this work we address the problem of predicting protein-protein interactions. Its solution can give greater insight in the study of complex diseases, like cancer, and provides valuable information in the study of active small molecules for new drugs, limiting the number of molecules to be tested in laboratory. We model the problem as a binary classification task, using a suitable coding of the amino acid sequences. We apply k-Nearest Neighbors classification algorithm to the classes of interacting and noninteracting proteins. Results show that it is possible to achieve high prediction accuracy in cross validation. A case study is analyzed to show it is possible to reconstruct a real network of thousands interacting proteins with high accuracy on standard hardware.

机译：在这项工作中，我们解决了预测蛋白质相互作用的问题。它的解决方案可以为诸如癌症等复杂疾病的研究提供更大的见识，并为新药的活性小分子研究提供有价值的信息，从而限制了要在实验室中测试的分子数量。我们使用氨基酸序列的适当编码将问题建模为二进制分类任务。我们将k-最近邻居分类算法应用于相互作用和非相互作用蛋白的类别。结果表明，在交叉验证中可以实现较高的预测准确性。案例分析表明，可以在标准硬件上高精度地重建数千种相互作用蛋白的真实网络。

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来源
《Computational intelligence methods for bioinformatics and biostatistics》|2009年|p.139-150|共12页
会议地点 Genoa(IT);Genoa(IT)
作者
Mario R. Guarracino; Adriano Nebbia;
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作者单位

High Performance Computing and Networking Institute (ICAR-CNR) National Research Council, Italy Via P. Castellino, 111 - 80131 Napoli (IT);

High Performance Computing and Networking Institute (ICAR-CNR) National Research Council, Italy Via P. Castellino, 111 - 80131 Napoli (IT);

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原文格式 PDF
正文语种 eng
中图分类生物工程学（生物技术）;人工智能理论;
关键词
protein-protein interaction prediction; conjoint-triad method; k-nearest neighbors; binary classification;

机译：蛋白质相互作用预测；三联法k近邻；二元分类;
入库时间 2022-08-26 14:04:25

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Predicting Protein-Protein Interactions with K-Nearest Neighbors Classification Algorithm

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