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

Samyabrata Sen, Indraneel Vairagare, Jitendrapuri Gosai, Abhishek Shrivastava

Abstract read

In one paragraph

Article in BMC bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Samyabrata Sen *Center for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.

Indraneel Vairagare *Center for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.

Jitendrapuri GosaiCenter for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.

Abhishek ShrivastavaCenter for Fundamental and Applied Microbiomics, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA. ashrivastava@asu.edu.

Funding

Mechanistic investigation of bacterial type 9 secretion system machinery and its involvement in gut metabolism and immunomodulationR35GM147131 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI Abhishek Shrivastava · 2022 to 2026

$2.0M

NIGMS NIH HHS R35 GM147131NIGMS NIH HHS R35GM147131

6 · The paper itself

Abstract

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.

Indexed as

Artificial IntelligenceBacteriaImage Processing, Computer-AssistedSoftwareBacterial motilityBacterial trackingCellular motilityChemotaxisComputational biologyQuantitative biology

Identifiers

PMID40383775

DOI10.1186/s12859-025-06145-w

PMCPMC12087136

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.