Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Claims regarding the fidelity of extracellular electrical recording from gastrointestinal muscles not validated suitably.

American journal of physiology. Gastrointestinal and liver physiology·2026
Same author

Brefeldin A induces apoptosis in cisplatin-resistant ovarian cancer cells independent of ABCC2-mediated drug efflux.

Toxicology and applied pharmacology·2026
Same author

Response to: comment on 'digital twins and multimodal artificial intelligence in spine care: a scoping review of concepts, evidence, and translational barriers'.

Spine deformity·2026
Same author

Response to: Comment on 'Risk prediction in spine surgery: a scoping review of traditional models, artificial intelligence, and the challenge of clinical translation'.

Spine deformity·2026
Same author

Digital twins and multimodal artificial intelligence in spine care: a scoping review of concepts, evidence, and translational barriers.

Spine deformity·2026
Same author

Making a case, for who is setting the pace: conductors, drummers or just jamming in multicellular organ systems?

The Journal of physiology·2026

Related Experiment Video

Updated: Dec 12, 2025

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
06:49

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Published on: June 16, 2014

17.5K

A high throughput machine-learning driven analysis of Ca2+ spatio-temporal maps.

Wesley A Leigh1, Guillermo Del Valle1, Sharif Amit Kamran2

  • 1Department of Physiology and Cell Biology, University of Nevada School of Medicine, Reno, NV 89557, USA.

Cell Calcium
|August 16, 2020
PubMed
Summary

This study introduces STMapAuto, a novel machine learning plugin for analyzing cellular calcium (Ca2+) imaging data. It automates spatio-temporal map analysis, significantly improving speed and accuracy for high-throughput research.

Keywords:
Ca(2+) Imaging analysisCa(2+) SignalingInterstitial cell of cajal

More Related Videos

Applications of Spatio-temporal Mapping and Particle Analysis Techniques to Quantify Intracellular Ca2+ Signaling In Situ
09:34

Applications of Spatio-temporal Mapping and Particle Analysis Techniques to Quantify Intracellular Ca2+ Signaling In Situ

Published on: January 7, 2019

9.6K
High-Throughput Analysis of Optical Mapping Data Using ElectroMap
07:36

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

Published on: June 4, 2019

9.9K

Related Experiment Videos

Last Updated: Dec 12, 2025

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
06:49

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Published on: June 16, 2014

17.5K
Applications of Spatio-temporal Mapping and Particle Analysis Techniques to Quantify Intracellular Ca2+ Signaling In Situ
09:34

Applications of Spatio-temporal Mapping and Particle Analysis Techniques to Quantify Intracellular Ca2+ Signaling In Situ

Published on: January 7, 2019

9.6K
High-Throughput Analysis of Optical Mapping Data Using ElectroMap
07:36

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

Published on: June 4, 2019

9.9K

Area of Science:

  • Cellular Biology
  • Biophysics
  • Computational Biology

Background:

  • High-resolution Ca2+ imaging generates large datasets requiring robust analysis.
  • Current spatio-temporal map (STMap) analysis methods are manual, time-consuming, and prone to user variability.
  • Standardized and accurate analysis is crucial for understanding cellular Ca2+ dynamics.

Purpose of the Study:

  • To develop an automated, machine learning-based plugin (STMapAuto) for analyzing Ca2+ STMaps.
  • To overcome limitations of manual STMap analysis, including time consumption and user error.
  • To enable high-throughput and consistent quantification of Ca2+ events.

Main Methods:

  • Development of a novel automated plugin, STMapAuto, implemented in Fiji.
  • Integration of optimized tools for Ca2+ signal preprocessing and automated segmentation.
  • Automated extraction of key Ca2+ event parameters (duration, spread, frequency, propagation, intensity).

Main Results:

  • STMapAuto accurately detects and quantifies Ca2+ transient parameters in various cell types, including Interstitial cells of Cajal (ICC).
  • The plugin demonstrated a 197-fold increase in analysis speed compared to the single pixel-line method for large datasets.
  • Automated analysis significantly reduces user error and enhances consistency.

Conclusions:

  • STMapAuto provides a standardized, accurate, and efficient method for analyzing Ca2+ STMap datasets.
  • The plugin facilitates high-throughput analysis, accelerating research into cellular Ca2+ behaviors.
  • This tool is valuable for researchers studying Ca2+ dynamics in diverse cell types.