Tttrlib:集成荧光光谱,成像和分子建模的模块化软件。

Thomas-Otavio Peulen, Katherina Hemmen, Annemarie Greife, Benjamin M Webb, Suren Felekyan, Andrej Sali, Claus A M Seidel, Hugo Sanabria, Katrin G Heinze
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引用次数: 0

摘要

摘要:我们引入了荧光单分子和图像光谱数据的读写和处理软件,并开发了分析管道,以统一各种光谱分析工具。我们的软件可用于处理多种实验类型,例如时间分辨单分子光谱,激光扫描显微镜,荧光相关光谱和图像相关光谱。该软件是文件格式无关的,并处理多种时间分辨的数据格式和输出。我们的软件消除了数据转换的需要,并减轻了数据存档问题。可用性和实现:tttrlib可通过pip (https://pypi.org/project/tttrlib/)和bioconda获得,而开源代码可通过GitHub (https://github.com/fluorescence-tools/tttrlib)获得。演示如何在体外和活细胞图像光谱分析的示例和附加文档可在https://docs.peulen.xyz/tttrlib和https://zenodo.org/records/14002224.Supplementary上获得信息:补充数据可在Bioinformatics在线获得。
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tttrlib: modular software for integrating fluorescence spectroscopy, imaging, and molecular modeling.

Summary: We introduce software for reading, writing and processing fluorescence single-molecule and image spectroscopy data and developing analysis pipelines to unify various spectroscopic analysis tools. Our software can be used for processing multiple experiment types, e.g. for time-resolved single-molecule spectroscopy, laser scanning microscopy, fluorescence correlation spectroscopy and image correlation spectroscopy. The software is file format agnostic and processes multiple time-resolved data formats and outputs. Our software eliminates the need for data conversion and mitigates data archiving issues.

Availability and implementation: tttrlib is available via pip (https://pypi.org/project/tttrlib/) and bioconda while the open-source code is available via GitHub (https://github.com/fluorescence-tools/tttrlib). Presented examples and additional documentation demonstrating how to implement in vitro and live-cell image spectroscopy analysis are available at https://docs.peulen.xyz/tttrlib and https://zenodo.org/records/14002224.

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