Recent surges in mass spectrometry-based proteomics studies demand a concurrent rise in speedy and optimized data processing tools and pipelines. Although several stand-alone bioinformatics tools exist that provide protein-protein interaction (PPI) data, we developed Protein Interaction Network Extractor (PINE) as a fully automated, user-friendly, graphical user interface application for visualization and exploration of global proteome and post-translational modification (PTM) based networks. PINE also supports overlaying differential expression, statistical significance thresholds, and PTM sites on functionally enriched visualization networks to gain insights into proteome-wide regulatory mechanisms and PTM-mediated networks. To illustrate the relevance of the tool, we explore the total proteome and its PTM-associated relationships in two different nonalcoholic steatohepatitis (NASH) mouse models to demonstrate different context-specific case studies. The strength of this tool relies in its ability to (1) perform accurate protein identifier mapping to resolve ambiguity, (2) retrieve interaction data from multiple publicly available PPI databases, and (3) assimilate these complex networks into functionally enriched pathways, ontology categories, and terms. Ultimately, PINE can be used as an extremely powerful tool for novel hypothesis generation to understand underlying disease mechanisms.

中文翻译：

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PINE：提取和可视化以蛋白质为中心的功能网络的自动化工具。


最近基于质谱的蛋白质组学研究的激增要求快速和优化的数据处理工具和管道同时增加。尽管存在一些提供蛋白质-蛋白质相互作用 (PPI) 数据的独立生物信息学工具，但我们开发了蛋白质相互作用网络提取器 (PINE) 作为全自动、用户友好的图形用户界面应用程序，用于可视化和探索全局蛋白质组和后期-基于翻译修饰（PTM）的网络。 PINE 还支持在功能丰富的可视化网络上叠加差异表达、统计显着性阈值和 PTM 位点，以深入了解蛋白质组范围的调控机制和 PTM 介导的网络。为了说明该工具的相关性，我们在两种不同的非酒精性脂肪性肝炎 (NASH) 小鼠模型中探索了总蛋白质组及其 PTM 相关关系，以展示不同的特定情况案例研究。该工具的优势在于其以下能力：(1) 执行准确的蛋白质标识符映射以解决歧义，(2) 从多个公开可用的 PPI 数据库检索交互数据，以及 (3) 将这些复杂网络同化为功能丰富的途径、本体类别和条款。最终，PINE 可以用作生成新假设的极其强大的工具，以了解潜在的疾病机制。