Bioinformatics Tools for Kinome Microarrays

磷酸化是细胞信号传导的基本机制。该反应涉及蛋白激酶（一种将磷酸基团添加到某些氨基酸的酶）和目标（底物）蛋白质。以高通量方式研究蛋白激酶的一种方法是使用激酶组微阵列，其由固定在载玻片上的数百或数千个探针组成。在暴露于制备的样品后，同时测量微阵列上的所有探针以获得样品中激酶磷酸化的证据，从而提供（潜在的）细胞磷酸化活性的“快照”。在过去的几年里，我们的团队开发了各种生物信息学工具来支持这项技术。我们设计了软件来帮助确定要用作物种特异性或路径特异性阵列的探针的肽，以及软件来过滤、调整、可视化和询问所得到的测量结果。我们还开发了用于协助评估激酶组数据分析软件的工具。与合作者一起，我们已经证明了该技术和软件在从植物到昆虫再到人类的生物体中的实用性，其应用范围从确定个体的“运动型”到研究埃博拉病毒感染的致病机制。然而，这一领域还远未成熟，仍有许多悬而未决的问题。拟议的研究计划的重点是解决目前的软件支持kinome微阵列技术的缺点，找到解决已知问题的方法，并开发新的，改进的算法和软件工具。具体来说，我们将开发改进的数据标准化技术，利用特殊的校准探针从微阵列中提取更多更好的信息，并利用我们独特的，广泛的数据收集，以改善激酶组微阵列技术和开发软件，导致发现以前未知的信号通路。

Phosphorylation is a fundamental mechanism of cellular signalling. The reaction involves a protein kinase (an enzyme that adds a phosphate group to certain amino acids) and a target (substrate) protein. One way to study protein kinases in a high-throughput manner is with kinome microarrays, which consist of hundreds or thousands of probes affixed to a glass slide. After exposure to a prepared sample, all the probes on the microarray are simultaneously measured for evidence of phosphorylation by kinases in the sample, providing a "snapshot" of (potential) cellular phosphorylation activity. Over the past several years, our group has developed various bioinformatics tools to support this technology. We have devised software to help determine the peptides to be used as probes for species-specific or pathway-specific arrays, and software to filter, adjust, visualize, and interrogate the resulting measurements. We have also developed tools for assisting with the evaluation of software for kinome data analysis. With collaborators, we have demonstrated the utility of the technology and software in organisms ranging from plants to insects to humans, with applications ranging from determining an individual's "kinotype" to studying pathogenic mechanisms of Ebola infection. However, the field is still far from mature, with many open questions remaining. The focus of the proposed research program is to address shortcomings of current software supporting kinome microarray technology, to find solutions to known problems, and to develop new, improved algorithms and software tools. Specifically, we will develop improved data normalization techniques, utilize special calibration probes to extract more and better information from the microarrays, and exploit our unique, wide-ranging collection of data to improve kinome microarray technology and to develop software that leads to the discovery of previously unknown signalling pathways.