Publications¶
The following publications have used TrajPy for trajectory analysis and classification. If you use TrajPy in your research, please cite the methodological paper and the software DOI listed below.
Citing TrajPy¶
Please cite the methodological paper and the software DOI in any academic work that uses TrajPy:
Methodological paper
Moreira-Soares, M., Mossmann, E., Travasso, R. D. M., and Bordin, J. R. TrajPy: empowering feature engineering for trajectory analysis across domains. Bioinformatics Advances, Volume 4, Issue 1, 2024, vbae026. doi:10.1093/bioadv/vbae026
Software DOI
Mauricio Moreira and Eduardo Mossmann. phydev/trajpy: TrajPy 1.3.1. Zenodo, 2020. doi:10.5281/zenodo.3978699
BibTeX entries:
@article{10.1093/bioadv/vbae026,
author = {Moreira-Soares, Maurício and Mossmann, Eduardo and Travasso, Rui D M and Bordin, José Rafael},
title = {TrajPy: empowering feature engineering for trajectory analysis across domains},
journal = {Bioinformatics Advances},
volume = {4},
number = {1},
pages = {vbae026},
year = {2024},
month = {02},
abstract = {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.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 in silico models for cell migration, in combination with image analysis.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.},
issn = {2635-0041},
doi = {10.1093/bioadv/vbae026},
url = {https://doi.org/10.1093/bioadv/vbae026},
eprint = {https://academic.oup.com/bioinformaticsadvances/article-pdf/4/1/vbae026/57296250/vbae026.pdf},
}
Publications using TrajPy¶
Journal Articles¶
Moreira-Soares, M., Mossmann, E., Travasso, R. D. M., and Bordin, J. R. TrajPy: empowering feature engineering for trajectory analysis across domains. Bioinformatics Advances, Volume 4, Issue 1, 2024, vbae026. doi:10.1093/bioadv/vbae026
Simões, R. F., Pino, R., Moreira-Soares, M., et al. Quantitative Analysis of Neuronal Mitochondrial Movement Reveals Patterns Resulting from Neurotoxicity of Rotenone and 6-Hydroxydopamine. FASEB Journal, 2021; 35:e22024. doi:10.1096/fj.202100899R
Moreira-Soares, M., Pinto-Cunha, S., Bordin, J. R., and Travasso, R. D. M. Adhesion modulates cell morphology and migration within dense fibrous networks. Journal of Physics: Condensed Matter, 2020. doi:10.1088/1361-648X/ab7c17
Dissertations¶
Eduardo Henrique Mossmann. A physics based feature engineering framework for trajectory analysis. MSc dissertation. Federal University of Pelotas, Brazil, 2022.