Department of Biomedical Engineering, The University of Texas at San Antonio, San Antonio, TX, 78249, USA.
Department of Biology, The University of Texas at San Antonio, San Antonio, TX, 78249, USA.
Neuroinformatics. 2017 Oct;15(4):333-342. doi: 10.1007/s12021-017-9337-x.
We developed software tools to download, extract features, and organize the Cell Types Database from the Allen Brain Institute (ABI) in order to integrate its whole cell patch clamp characterization data into the automated modeling/data analysis cycle. To expand the potential user base we employed both Python and MATLAB. The basic set of tools downloads selected raw data and extracts cell, sweep, and spike features, using ABI's feature extraction code. To facilitate data manipulation we added a tool to build a local specialized database of raw data plus extracted features. Finally, to maximize automation, we extended our NeuroManager workflow automation suite to include these tools plus a separate investigation database. The extended suite allows the user to integrate ABI experimental and modeling data into an automated workflow deployed on heterogeneous computer infrastructures, from local servers, to high performance computing environments, to the cloud. Since our approach is focused on workflow procedures our tools can be modified to interact with the increasing number of neuroscience databases being developed to cover all scales and properties of the nervous system.
我们开发了软件工具,用于从艾伦脑科学研究所(Allen Brain Institute,ABI)下载、提取特征并组织细胞类型数据库,以便将其全细胞膜片钳特征数据整合到自动化建模/数据分析周期中。为了扩大潜在用户群,我们同时使用了 Python 和 MATLAB。基本工具集下载选定的原始数据并提取细胞、扫描和尖峰特征,使用 ABI 的特征提取代码。为了方便数据处理,我们添加了一个工具来构建原始数据加提取特征的本地专用数据库。最后,为了实现最大程度的自动化,我们扩展了我们的 NeuroManager 工作流自动化套件,以包含这些工具以及一个单独的调查数据库。扩展套件允许用户将 ABI 的实验和建模数据集成到部署在异构计算机基础架构上的自动化工作流中,从本地服务器到高性能计算环境再到云。由于我们的方法侧重于工作流程序,因此我们的工具可以进行修改,以与越来越多的正在开发的神经科学数据库交互,这些数据库涵盖了神经系统的所有尺度和特性。