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

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 years,...
Circadian Rhythms and Gene Regulation02:19

Circadian Rhythms and Gene Regulation

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 years,...
Harmonic Mean01:09

Harmonic Mean

The arithmetic mean is usually skewed towards the larger values in the data set. Therefore, to avoid this inherent bias towards smaller values, the harmonic mean is used.
Take the example of the speed of a car, which is the measure of the rate of distance traveled. If the vehicle traverses the same distance back-and-forth, its average speed equals the total distance traveled divided by the total time taken. However, if the car moves with varying speeds, then the arithmetic mean is more skewed...
Biological Clocks and Seasonal Responses02:45

Biological Clocks and Seasonal Responses

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.
Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response01:15

Chronopharmacokinetics: Circadian Rhythms and Influence on Drug Response

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...

You might also read

Related Articles

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

Sort by
Same author

PARP inhibition combined with a T-cell receptor β chain-directed antibody fusion molecule drives polyclonal antitumor immunity and tumor regression.

Journal for immunotherapy of cancer·2026
Same author

Docetaxel enhances Vβ-directed T-cell activation and antitumor immunity mediated by a bifunctional TCR agonist in breast and prostate cancer models.

Frontiers in immunology·2026
Same author

Assessing contribution of effect in oncology combination therapies: lessons learned to inform and optimize future registrational trial designs.

The oncologist·2026
Same author

Atomically dispersed iron on carbon nitride with enhanced oxygen adsorption for efficient and scalable photooxidation.

Nature communications·2026
Same author

KNOX II Transcription Factor HOS59 Regulates Gypsy Transposable Elements to Modulate Panicle Development in Rice.

Plant, cell & environment·2026
Same author

An EGFR co-amplified lncRNA HELDR promotes glioblastoma malignancy through KAT7-driven gene programs.

Nature cell biology·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
Same journal

EDEL: Enhancing Dense Retrievers for Curation of Biomedical Knowledge Bases.

Bioinformatics (Oxford, England)·2026
Same journal

Informative Relational Learning for Adverse Reaction Prediction with Enhanced Generalization to Novel Drugs.

Bioinformatics (Oxford, England)·2026
Same journal

An interpretable deep learning framework uncovers features governing CRISPR-Cas9 genome-editing efficiency.

Bioinformatics (Oxford, England)·2026
Same journal

3DICE: Interpretable 3D Cross-Modal Learning for Drug-Target Interaction Prediction and Large-Scale Drug Discovery.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jun 12, 2026

Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures
06:53

Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures

Published on: November 11, 2016

Analyzing circadian expression data by harmonic regression based on autoregressive spectral estimation.

Rendong Yang1, Zhen Su

  • 1Division of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100193, China.

Bioinformatics (Oxford, England)
|June 10, 2010
PubMed
Summary
This summary is machine-generated.

A new algorithm, ARSER, enhances the identification of circadian-regulated genes from noisy microarray data. This method improves the discovery of rhythmic gene expression patterns, offering new insights into biological clocks.

More Related Videos

A Computational Method to Quantify Fly Circadian Activity
13:05

A Computational Method to Quantify Fly Circadian Activity

Published on: October 28, 2017

A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

Related Experiment Videos

Last Updated: Jun 12, 2026

Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures
06:53

Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures

Published on: November 11, 2016

A Computational Method to Quantify Fly Circadian Activity
13:05

A Computational Method to Quantify Fly Circadian Activity

Published on: October 28, 2017

A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

Area of Science:

  • * Bioinformatics
  • * Computational Biology
  • * Genomics

Background:

  • * Circadian rhythms are fundamental biological processes found in most organisms.
  • * Identifying circadian-regulated genes is key to understanding clock-controlled pathways.
  • * Analyzing temporal microarray data for rhythmic patterns is challenging due to noise and limited sampling.

Purpose of the Study:

  • * To develop a robust algorithm for identifying rhythmic gene expression profiles from temporal microarray data.
  • * To improve the characterization of circadian-regulated genes, especially non-sinusoidal patterns.
  • * To provide a tool for deeper insights into the molecular mechanisms of circadian rhythms.

Main Methods:

  • * Proposed ARSER (Autoregressive Spectral Estimation and Regression) algorithm.
  • * Combines time and frequency domain analyses for periodicity detection.
  • * Utilizes harmonic regression to model rhythmic patterns and estimates period, phase, amplitude, and mean level.

Main Results:

  • * ARSER outperforms existing methods (COSOPT, Fisher's G-test) on simulated and real data.
  • * Successfully identified sinusoidal and non-sinusoidal periodic patterns in short, noisy time-series.
  • * Discovered novel non-sinusoidal periodic transcripts in Arabidopsis, advancing circadian rhythm research.

Conclusions:

  • * ARSER provides a superior method for analyzing noisy, short time-series microarray data.
  • * The algorithm facilitates the discovery of previously undetected circadian-regulated genes.
  • * Findings offer new perspectives on the molecular basis of circadian rhythms.