AXZ查看器:用于可视化未处理的AFM - IR数据的web应用程序。

IF 5.4
Wouter Duverger, Georg Ramer, Nikolaos Louros, Joost Schymkowitz, Frederic Rousseau
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引用次数: 0

摘要

动机:基于原子力显微镜的红外光谱(AFM - IR)是一种新颖的创新方法,用于无标签的高分辨率结构生物学。然而,AFM - IR仪器生成的数据文件的性质阻碍了传统开源科学图像分析软件套件的调查。因此,AFM - IR数据集的报告没有标准化,数据本身也难以审计。结果:我们开发了一个web应用程序,任何人都可以轻松地打开、查看和审计原始AFM - IR数据文件,而无需深入了解该方法。它还暴露了显微镜在测量时记录的所有元数据。web应用程序基于Python包,支持科学Python生态系统中的自定义数据分析。该工具为AFM - IR数据审查提供了一个可访问的、透明的解决方案,具有支持AFM - IR研究的可重复性和标准化的潜力,并鼓励更广泛地采用这种创新的光谱方法。可用性:web应用程序托管在https://anasys-python-tools-gui.streamlit.app。其源代码列于https://github.com/wduverger/anasys-python-tools-gui。底层Python包可从https://github.com/GeorgRamer/anasys-python-tools获得,可以使用pip进行安装。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AXZ viewer: a web application to visualize unprocessed AFM-IR data.

Motivation: Atomic Force Microscopy-based Infrared spectroscopy (AFM-IR) is a novel and innovative method for label-free high-resolution structural biology. However, the nature of the data files generated by AFM-IR instruments precludes investigation by conventional open-source scientific image analysis software suites. As a result, reporting of AFM-IR datasets is not standardized and the data itself is difficult to audit.

Results: We have developed a web application that allows anyone to open, review, and audit raw AFM-IR data files easily and without deep knowledge of the method. It also exposes all metadata recorded by the microscope at the time of measurement. The web application is based on a Python package that supports custom data analyses within the scientific Python ecosystem. This tool provides an accessible, transparent solution for AFM-IR data review, with the potential to support reproducibility and standardization in AFM-IR research and encourage wider adoption of this innovative spectroscopy method.

Availability and implementation: The web app is hosted at https://anasys-python-tools-gui.streamlit.app. Its source code is listed at https://github.com/wduverger/anasys-python-tools-gui. The underlying Python package is available at https://github.com/GeorgRamer/anasys-python-tools and can be installed using pip.

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