利用Pycytominer进行可重复的基于图像的分析。

IF 32.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Nature Methods Pub Date : 2025-03-03 DOI:10.1038/s41592-025-02611-8
Erik Serrano, Srinivas Niranj Chandrasekaran, Dave Bunten, Kenneth I. Brewer, Jenna Tomkinson, Roshan Kern, Michael Bornholdt, Stephen J. Fleming, Ruifan Pei, John Arevalo, Hillary Tsang, Vincent Rubinetti, Callum Tromans-Coia, Tim Becker, Erin Weisbart, Charlotte Bunne, Alexandr A. Kalinin, Rebecca Senft, Stephen J. Taylor, Nasim Jamali, Adeniyi Adeboye, Hamdah Shafqat Abbasi, Allen Goodman, Juan C. Caicedo, Anne E. Carpenter, Beth A. Cimini, Shantanu Singh, Gregory P. Way
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引用次数: 0

摘要

高通量显微镜技术的进步使得能够快速获取大量高含量的显微镜图像。其次,无论是通过深度学习还是经典算法,图像分析管道通常都会产生单细胞特征。为了处理这些单细胞的下游应用,我们提出Pycytominer,这是一个用户友好的开源Python包,实现了基于图像分析的生物信息学步骤的关键。我们在机器学习项目中展示了Pycytominer的有用性,以预测导致不良细胞损伤的有害化合物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Reproducible image-based profiling with Pycytominer
Advances in high-throughput microscopy have enabled the rapid acquisition of large numbers of high-content microscopy images. Next, whether by deep learning or classical algorithms, image analysis pipelines commonly produce single-cell features. To process these single cells for downstream applications, we present Pycytominer, a user-friendly, open-source Python package that implements the bioinformatics steps key to image-based profiling. We demonstrate Pycytominer’s usefulness in a machine-learning project to predict nuisance compounds that cause undesirable cell injuries. Pycytominer is a user-friendly, open-source Python package that carries out key bioinformatics steps in image-based profiling.
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来源期刊
Nature Methods
Nature Methods 生物-生化研究方法
CiteScore
58.70
自引率
1.70%
发文量
326
审稿时长
1 months
期刊介绍: Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.
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