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使用独立数据集对蛋白质磷酸化位点预测器进行分析。

Analysis of protein phosphorylation site predictors with an independent dataset.

作者信息

Sikder Abdur R, Zomaya Albert Y

机构信息

International Computer Science Institute, 1947 Center Street, Suite 600, Berkeley, CA 94704, USA.

出版信息

Int J Bioinform Res Appl. 2009;5(1):20-37. doi: 10.1504/IJBRA.2009.022461.

Abstract

Protein phosphorylation plays a fundamental role in most of the cellular regulatory pathways. Experimental detection of protein phosphorylation sites is labour intensive and often limited by the availability and optimisation of enzymatic reactions. The in silico prediction of phosphorylation sites using protein's primary sequences may provide guidelines for further experimental consideration and interpretation of phosphoproteomic data. An array of such tools exists over the internet and provides the prediction for protein kinase families. We developed an independent dataset to compare the performances of these methods to provide scientists with a better understanding of which method to use for their research.

摘要

蛋白质磷酸化在大多数细胞调节途径中起着基础性作用。蛋白质磷酸化位点的实验检测工作强度大,且常常受到酶促反应可用性和优化的限制。利用蛋白质一级序列对磷酸化位点进行计算机预测可为进一步的实验考量和磷酸化蛋白质组学数据的解读提供指导。互联网上有一系列此类工具,可对蛋白激酶家族进行预测。我们开发了一个独立数据集来比较这些方法的性能,以便为科学家更好地了解哪种方法适用于他们的研究提供帮助。

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