蛋白质翻译后修饰磷酸化位点预测工具 —— GPS 2.0

GPS2.0是一款用于预测特定蛋白激酶磷酸化位点的软件,能够针对408种人类蛋白激酶进行层级化的预测。该软件采用了一种简单的方法来估算理论上最大的假阳性率,并对超过13,000个哺乳动物磷酸化位点进行了大规模预测。此外,还提供了Aurora-B特异性底物的全蛋白质组预测,包括蛋白质-蛋白质相互作用信息。

 GPS 2.0, a Tool to Predict Kinase-specific Phosphorylation Sites in Hierarchy
  Yu Xue , Jian Ren , Xinjiao Gao, Changjiang Jin, Longping Wen, and Xuebiao Yao
 Mol Cell Proteomics.2008 ; 7: 1598-1608

  [Abstract] [Full Text] [Supplemental Data]

Computational prediction of phosphorylation sites with their cognate protein kinases (PKs) is greatly helpful for further experimental design. Although ~10 online predictors were developed, the PK classification and control of false positive rate (FPR ) were not well addressed. Here we adopted a well-established rule to classify PKs into a hierarchical structure with four levels. Also, we developed a simple approach to estimate the theoretically maximal FPRs. Then GPS 2.0 (Group-based Prediction System , ver 2.0 ) software was implemented in JAVA and could predict kinase-specific phosphorylation sites for 408 human PKs in hierarchy. As an application, we performed a large-scale prediction of >13,000 mammalian phosphorylation sites with high performances. In addition, we also provided a proteome-wide prediction of Aurora-B specific substrates including protein-protein interaction information. As the first stand-alone software for computational phosphorylation, GPS 2.0 will be an excellent tool for further experimental consideration and construction of phosphorylation networks.

The GPS 2.0 is freely available at: http://gps.biocuckoo.org

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GPS 2.0 GUI

GPS 2.0 User Interface

【无线传感器】使用 MATLAB和 XBee连续监控温度传感器无线网络研究(Matlab代码实现)内容概要:本文围绕使用MATLAB和XBee技术实现温度传感器无线网络的连续监控展开研究,介绍了如何构建无线传感网络系统,并利用MATLAB进行数据采集、处理与可视化分析。系统通过XBee模块实现传感器节点间的无线通信,实时传输温度数据至主机,MATLAB负责接收并处理数据,实现对环境温度的动态监测。文中详细阐述了硬件连接、通信协议配置、数据解析及软件编程实现过程,并提供了完整的MATLAB代码示例,便于读者复现和应用。该方案具有良好的扩展性和实用性,适用于远程环境监测场景。; 适合人群:具备一定MATLAB编程基础和无线通信基础知识的高校学生、科研人员及工程技术人员,尤其适合从事物联网、传感器网络相关项目开发的初学者与中级开发者。; 使用场景及目标:①实现基于XBee的无线温度传感网络搭建;②掌握MATLAB与无线模块的数据通信方法;③完成实时数据采集、处理与可视化;④为环境监测、工业测控等实际应用场景提供技术参考。; 阅读建议:建议读者结合文中提供的MATLAB代码与硬件连接图进行实践操作,先从简单的点对点通信入手,逐步扩展到多节点网络,同时可进一步探索数据滤波、异常检测、远程报警等功能的集成。
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