• RABiTPy: an open-source Python...

Treffer: RABiTPy: an open-source Python software for rapid, AI-powered bacterial tracking and analysis.

Title:
RABiTPy: an open-source Python software for rapid, AI-powered bacterial tracking and analysis.
Authors:
Sen S; Center for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.; School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA.; Center for Biological Physics, Arizona State University, Tempe, AZ, 85287, USA., Vairagare I; Center for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.; School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA.; Center for Biological Physics, Arizona State University, Tempe, AZ, 85287, USA.; School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, 85287, USA., Gosai J; Center for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.; School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA.; Center for Biological Physics, Arizona State University, Tempe, AZ, 85287, USA., Shrivastava A; Center for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA. ashrivastava@asu.edu.; School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA. ashrivastava@asu.edu.; Center for Biological Physics, Arizona State University, Tempe, AZ, 85287, USA. ashrivastava@asu.edu.
Source:
BMC bioinformatics [BMC Bioinformatics] 2025 May 18; Vol. 26 (1), pp. 127. Date of Electronic Publication: 2025 May 18.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105 (Electronic) Linking ISSN: 14712105 NLM ISO Abbreviation: BMC Bioinformatics Subsets: MEDLINE
Imprint Name(s):
Original Publication: [London] : BioMed Central, 2000-
MeSH Terms:
Software* , Artificial Intelligence* , Image Processing, Computer-Assisted*/methods , Bacteria*
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Grant Information:
R35 GM147131 United States GM NIGMS NIH HHS; R35GM147131 United States GM NIGMS NIH HHS
Contributed Indexing:
Keywords: Bacterial motility; Bacterial tracking; Cellular motility; Chemotaxis; Computational biology; Quantitative biology
Entry Date(s):
Date Created: 20250518 Date Completed: 20250518 Latest Revision: 20250521
Update Code:
20250521
PubMed Central ID:
PMC12087136
DOI:
10.1186/s12859-025-06145-w
PMID:
40383775
Database:
MEDLINE

Weitere Informationen

Bacterial tracking is crucial for understanding the mechanisms governing motility, chemotaxis, cell division, biofilm formation, and pathogenesis. Although modern microscopy and computing have enabled the collection of large datasets, many existing tools struggle with big data processing or with accurately detecting, segmenting, and tracking bacteria of various shapes. To address these issues, we developed RABiTPy, an open-source Python software pipeline that integrates traditional and artificial intelligence-based segmentation with tracking tools within a user-friendly framework. RABiTPy runs interactively in Jupyter notebooks and supports numerous image and video formats. Users can select from adaptive, automated thresholding, or AI-based segmentation methods, fine-tuning parameters to fit their needs. The software offers customizable parameters to enhance tracking efficiency, and its streamlined handling of large datasets offers an alternative to existing tracking software by emphasizing usability and modular integration. RABiTPy supports GPU and CPU processing as well as cloud computing. It offers comprehensive spatiotemporal analyses that includes trajectories, motile speeds, mean squared displacement, and turning angles-while providing a variety of visualization options. With its scalable and accessible platform, RABiTPy empowers researchers, even those with limited coding experience, to analyze bacterial physiology and behavior more effectively. By reducing technical barriers, this tool has the potential to accelerate discoveries in microbiology.
(© 2025. The Author(s).)

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Availability and requirements: Project name: RABiTPy: Project home page: https://pypi.org/project/RABiTPy/ : Operating system(s): Platform independent: Programming language: Python: Other requirements: Python less that 3.11, greater than or equal to 3.10: License: MIT license: Any restrictions to use by non-academics: license needed. Competing interests: The authors declare no competing interests.