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TrajPy:助力跨领域轨迹分析的特征工程

TrajPy: empowering feature engineering for trajectory analysis across domains.

作者信息

Moreira-Soares Maurício, Mossmann Eduardo, Travasso Rui D M, Bordin José Rafael

机构信息

Oslo Centre for Biostatistics and Epidemiology, University of Oslo, Oslo, 0373, Norway.

Centre for Bioinformatics, University of Oslo, Oslo, 0373, Norway.

出版信息

Bioinform Adv. 2024 Feb 23;4(1):vbae026. doi: 10.1093/bioadv/vbae026. eCollection 2024.

Abstract

MOTIVATION

Trajectories, which are sequentially measured quantities that form a path, are an important presence in many different fields, from hadronic beams in physics to electrocardiograms in medicine. Trajectory analysis requires the quantification and classification of curves, either by using statistical descriptors or physics-based features. To date, no extensive and user-friendly package for trajectory analysis has been readily available, despite its importance and potential application across various domains.

RESULTS

We have developed TrajPy, a free, open-source Python package that serves as a complementary tool for empowering trajectory analysis. This package features a user-friendly graphical user interface and offers a set of physical descriptors that aid in characterizing these complex structures. TrajPy has already been successfully applied to studies of mitochondrial motility in neuroblastoma cell lines and the analysis of models for cell migration, in combination with image analysis.

AVAILABILITY AND IMPLEMENTATION

The TrajPy package is developed in Python 3 and is released under the GNU GPL-3.0 license. It can easily be installed via PyPi, and the development source code is accessible at the repository: https://github.com/ocbe-uio/TrajPy/. The package release is also automatically archived with the DOI 10.5281/zenodo.3656044.

摘要

动机

轨迹是按顺序测量的量,它们形成一条路径,在许多不同领域都有重要体现,从物理学中的强子束到医学中的心电图。轨迹分析需要通过使用统计描述符或基于物理的特征对曲线进行量化和分类。尽管轨迹分析在各个领域都很重要且有潜在应用,但到目前为止,还没有一个广泛且用户友好的轨迹分析软件包。

结果

我们开发了TrajPy,这是一个免费的开源Python软件包,可作为增强轨迹分析的补充工具。该软件包具有用户友好的图形用户界面,并提供了一组有助于表征这些复杂结构的物理描述符。TrajPy已经成功应用于神经母细胞瘤细胞系中线粒体运动性的研究以及结合图像分析的细胞迁移模型分析。

可用性和实现方式

TrajPy软件包是用Python 3开发的,根据GNU GPL - 3.0许可发布。它可以通过PyPi轻松安装,开发源代码可在以下存储库中获取:https://github.com/ocbe - uio/TrajPy/。该软件包版本也会自动存档,其数字对象标识符(DOI)为10.5281/zenodo.3656044。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ea53/11032726/e4c24dc08368/vbae026f1.jpg

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