Pizzirusso Giusy, Sundström Simon, Arroyo-García Luis Enrique
Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, 17177, Solna, Sweden.
Department of Women'S and Children'S Health, Karolinska Institutet, 17177, Solna, Sweden.
Neuroinformatics. 2025 Mar 18;23(2):24. doi: 10.1007/s12021-025-09721-w.
Patch-clamp recordings are vital for investigating the electrical properties of excitable cells, yet the analysis of these recordings often involves time-consuming manual procedures prone to variability. To address this challenge, we developed the Auto ANT (Automated Analysis and Tables) open-source software, an automated, user-friendly graphical interface for the extraction of firing properties and passive membrane properties from patch-clamp recordings. Thanks to the novel built-in automation feature, Auto ANT enables batch analysis of multiple files recorded with the same protocol in minutes. Our tool is designed to streamline data analysis, providing a fast, efficient, and reproducible alternative to manual methods. With a focus on accessibility, Auto ANT allows the users to perform precise comprehensive electrophysiological analyses without requiring programming expertise. By combining automation with a user-centric design, Auto ANT offers a valuable resource for researchers to accelerate data analysis while promoting consistency and reproducibility across different studies.
膜片钳记录对于研究可兴奋细胞的电特性至关重要,然而这些记录的分析通常涉及耗时的手动操作,且容易出现变异性。为应对这一挑战,我们开发了Auto ANT(自动分析与表格)开源软件,这是一个自动化、用户友好的图形界面,用于从膜片钳记录中提取放电特性和被动膜特性。得益于新颖的内置自动化功能,Auto ANT能够在几分钟内对使用相同协议记录的多个文件进行批量分析。我们的工具旨在简化数据分析,为手动方法提供快速、高效且可重复的替代方案。以易用性为重点,Auto ANT允许用户在无需编程专业知识的情况下进行精确的全面电生理分析。通过将自动化与以用户为中心的设计相结合,Auto ANT为研究人员提供了宝贵的资源,可加速数据分析,同时促进不同研究之间的一致性和可重复性。