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

Circadian Rhythms and Gene Regulation02:19

Circadian Rhythms and Gene Regulation

4.7K
The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent...
4.7K
Circadian Rhythms and Gene Regulation02:19

Circadian Rhythms and Gene Regulation

2.5K
2.5K
Biological Clocks and Seasonal Responses02:45

Biological Clocks and Seasonal Responses

42.0K
The circadian—or biological—clock is an intrinsic, timekeeping, molecular mechanism that allows plants to coordinate physiological activities over 24-hour cycles called circadian rhythms. Photoperiodism is a collective term for the biological responses of plants to variations in the relative lengths of dark and light periods. The period of light-exposure is called the photoperiod.
42.0K
Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response01:15

Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response

440
Circadian rhythms are cyclic changes that are crucial in plasma drug concentrations. Various standard circadian parameters, including core body temperature, heart rate, and other cardiovascular factors, directly impact disease states and the therapeutic response to drug therapy.
The time of drug administration is an important factor to consider, as it can influence the toxic dose of a drug. For example, a study conducted by Prins et al. in 1997 examined the effects of the timing of...
440
Understanding Sleep01:11

Understanding Sleep

1.8K
Sleep, an essential biological state, involves significant reductions in physical activity, sensory awareness, and interaction with the environment. This complex physiological process is primarily regulated by specific brain regions, notably the hypothalamus and pons, which govern the sleep-wake cycle or circadian rhythm.
The circadian rhythm, a nearly 24-hour cycle, is deeply influenced by environmental light cues. Light exposure directly affects the hypothalamus, which in turn regulates...
1.8K
Neural Control of Respiration01:18

Neural Control of Respiration

5.5K
The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...
5.5K

You might also read

Related Articles

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

Sort by
Same author

Biomarker screen-guided care for preterm birth risk in nulliparous pregnancies: a subgroup analysis of the PRIME randomized controlled trial.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians·2026
Same author

Scaling Up Bayesian Neural Networks with Neural Networks.

Transactions on machine learning research·2026
Same author

Immune checkpoint blockade augments lymphodepleting chemotherapy-induced antitumor immunity by expanding effector CD8+ T cell clones.

Cancer research·2026
Same author

A Bayesian Time-Varying Psychophysiological Interaction Model.

Data science in science·2026
Same author

Neurodatascience: Past, Present, and Future.

Data science in science·2026
Same author

A HORSESHOE MIXTURE MODEL FOR BAYESIAN SCREENING WITH AN APPLICATION TO LIGHT SHEET FLUORESCENCE MICROSCOPY IN BRAIN IMAGING.

The annals of applied statistics·2026

Related Experiment Video

Updated: Mar 19, 2026

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents
05:46

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents

Published on: January 24, 2013

22.3K

What time is it? Deep learning approaches for circadian rhythms.

Forest Agostinelli1, Nicholas Ceglia1, Babak Shahbaba2

  • 1Department of Computer Science.

Bioinformatics (Oxford, England)
|June 17, 2016
PubMed
Summary

This study introduces BIO_CYCLE and BIO_CLOCK, deep learning tools for analyzing circadian rhythms in biological data. These systems accurately identify oscillating signals and estimate experimental time points, advancing high-throughput circadian research.

More Related Videos

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
08:36

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Published on: August 8, 2019

12.9K
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.9K

Related Experiment Videos

Last Updated: Mar 19, 2026

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents
05:46

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents

Published on: January 24, 2013

22.3K
Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
08:36

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Published on: August 8, 2019

12.9K
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.9K

Area of Science:

  • Computational Biology
  • Genomics
  • Systems Biology

Background:

  • Circadian rhythms are fundamental biological processes present in nearly all species.
  • Modern high-throughput technologies generate complex time-series data for circadian studies.
  • Analyzing this data presents computational challenges in identifying oscillations and time of measurement.

Purpose of the Study:

  • To develop computational tools for robustly analyzing high-throughput circadian data.
  • To accurately identify periodic biological signals within circadian experiments.
  • To precisely estimate the time of transcriptomic experiments using core clock gene expression.

Main Methods:

  • Curated synthetic and biological time-series datasets for training and validation.
  • Deep learning models were developed and trained for signal periodicity detection (BIO_CYCLE).
  • Deep learning models were developed and trained for time-point estimation (BIO_CLOCK).

Main Results:

  • BIO_CYCLE achieved state-of-the-art performance in identifying oscillating signals and their parameters.
  • BIO_CLOCK accurately estimates experimental time points within approximately 1 hour using minimal gene data.
  • BIO_CLOCK demonstrated robustness across different tissue types and experimental conditions.

Conclusions:

  • BIO_CYCLE and BIO_CLOCK offer powerful computational solutions for circadian biology research.
  • These tools enhance the analysis of high-throughput transcriptomic and other omics data.
  • The developed systems facilitate a deeper understanding of circadian regulation in biological systems.