Mass spectrometry-based phosphoproteomics is becoming an essential methodology for the study of global cellular signaling. Numerous bioinformatics resources are available to facilitate the translation of phosphopeptide identification and quantification results into novel biological and clinical insights, a critical step in phosphoproteomics data analysis. These resources include knowledge bases of kinases and phosphatases, phosphorylation sites, kinase inhibitors, and sequence variants affecting kinase function, and bioinformatics tools that can predict phosphorylation sites in addition to the kinase that phosphorylates them, infer kinase activity, and predict the effect of mutations on kinase signaling. However, these resources exist in silos and it is challenging to select among multiple resources with similar functions. Therefore, we put together a comprehensive collection of resources related to phosphoproteomics data interpretation, compared the use of tools with similar functions, and assessed the usability from the standpoint of typical biologists or clinicians. Overall, tools could be improved by standardization of enzyme names, flexibility of data input and output format, consistent maintenance, and detailed manuals.

中文翻译：

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使用磷酸化蛋白质组学数据了解细胞信号传导：生物信息学资源的全面指南。

基于质谱的磷酸化蛋白质组学正在成为研究全球细胞信号转导的重要方法。大量的生物信息学资源可用于将磷酸肽的鉴定和定量结果转化为新颖的生物学和临床见解，这是磷酸蛋白质组学数据分析的关键步骤。这些资源包括激酶和磷酸酶的知识库，磷酸化位点，激酶抑制剂和影响激酶功能的序列变体，以及可预测磷酸化位点的生物信息学工具，以及使磷酸化位点的激酶，推断激酶活性并预测突变效果的生物信息学工具。在激酶信号传导上 但是，这些资源存在于孤岛中，因此在具有相似功能的多个资源中进行选择具有挑战性。因此，我们收集了与磷酸蛋白质组学数据解释相关的资源的全面收集，比较了具有类似功能的工具的使用，并从典型的生物学家或临床医生的角度评估了可用性。总体而言，可以通过酶名称的标准化，数据输入和输出格式的灵活性，一致的维护以及详细的手册来改进工具。