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

Sinusoidal Sources01:18

Sinusoidal Sources

1.2K
Direct current (DC) refers to an electric current that flows in a single direction, maintaining a constant polarity. This is in contrast to alternating current (AC), which periodically changes its direction and magnitude. AC forms the backbone of modern electricity transmission and distribution systems due to its efficient long-distance transmission capabilities.
In homes, the power supplies use sinusoidal sources to provide electricity. These sources generate a voltage that varies sinusoidally...
1.2K
Exponential and Sinusoidal Signals01:18

Exponential and Sinusoidal Signals

765
The exponential function is crucial for characterizing waveforms that rise and decay rapidly. This continuous-time exponential function is defined using exponential terms with constants α and A. When both constants are real, the function is represented as,
765
Modeling with Differential Equations01:25

Modeling with Differential Equations

98
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
98
Graphical and Analytic Representation of Sinusoids01:20

Graphical and Analytic Representation of Sinusoids

1.0K
Analyzing two sinusoidal voltages with equal amplitude and period but different phases on an oscilloscope, an instrument used to display and analyze waveforms, involves a three-step process.
The first step is measuring the peak-to-peak value, which is twice the amplitude of the sinusoid. This provides information about the maximum voltage swing of the waveform.
Secondly, the period and angular frequency are determined. The period is the time taken for one complete cycle of the waveform, while...
1.0K
Classification of Systems-II01:31

Classification of Systems-II

520
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
520
Biological Clocks and Seasonal Responses02:45

Biological Clocks and Seasonal Responses

41.8K
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.
41.8K

You might also read

Related Articles

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

Sort by
Same author

A. salmonicida infection inhibits rainbow trout gill mucin production.

Fish & shellfish immunology·2025
Same author

Bridging worlds: connecting glycan representations with glycoinformatics via Universal Input and a canonicalized nomenclature.

Bioinformatics advances·2025
Same author

GlyContact analyzes glycan 3D structures at scale.

Nature communications·2025
Same author

Seal milk oligosaccharides rival human milk complexity and exhibit functional dynamics during lactation.

Nature communications·2025
Same author

Serum N-glycosylation is altered in Nephropathic Cystinosis.

Glycobiology·2025
Same author

Compositional data analysis enables statistical rigor in comparative glycomics.

Nature communications·2025
Same journal

MOREshiny: a user-friendly application for the inference of phenotype-specific multi-omic regulatory networks.

Bioinformatics advances·2026
Same journal

spammR: an R package designed for analysis and integration of spatial multi-omic measurements.

Bioinformatics advances·2026
Same journal

Interpretable prediction and generation of ASC-speck aptamers using multiscale deep biological learning models.

Bioinformatics advances·2026
Same journal

vClassifier: a toolkit for high-resolution phylogenetic classification of prokaryotic viruses.

Bioinformatics advances·2026
Same journal

GWAIS-Web: a free and secure web service for ultra-fast and large-scale genome-wide association interaction studies.

Bioinformatics advances·2026
Same journal

Folding the unfoldable 2: using AlphaFold and ESMFold to explore spurious proteins.

Bioinformatics advances·2026
See all related articles

Related Experiment Video

Updated: Feb 17, 2026

A Computational Method to Quantify Fly Circadian Activity
13:05

A Computational Method to Quantify Fly Circadian Activity

Published on: October 28, 2017

6.3K

PyCycleBio: modelling non-sinusoidal-oscillator systems in temporal biology.

Alexander R Bennett1, George Birchenough1,2, Daniel Bojar2,3

  • 1Department of Medical Biochemistry, Institute of Biomedicine, University of Gothenburg, 41390 Gothenburg, Sweden.

Bioinformatics Advances
|February 16, 2026
PubMed
Summary
This summary is machine-generated.

PyCycleBio integrates harmonic oscillator and Cosinor models for robust biological rhythm analysis. This new platform enhances sensitivity for transcriptomics, proteomics, and metabolomics data, advancing chronobiology.

More Related Videos

A Microfluidics Approach for the Functional Investigation of Signaling Oscillations Governing Somitogenesis
08:06

A Microfluidics Approach for the Functional Investigation of Signaling Oscillations Governing Somitogenesis

Published on: March 19, 2021

3.3K
An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions
07:59

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Published on: March 22, 2018

8.2K

Related Experiment Videos

Last Updated: Feb 17, 2026

A Computational Method to Quantify Fly Circadian Activity
13:05

A Computational Method to Quantify Fly Circadian Activity

Published on: October 28, 2017

6.3K
A Microfluidics Approach for the Functional Investigation of Signaling Oscillations Governing Somitogenesis
08:06

A Microfluidics Approach for the Functional Investigation of Signaling Oscillations Governing Somitogenesis

Published on: March 19, 2021

3.3K
An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions
07:59

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Published on: March 22, 2018

8.2K

Area of Science:

  • Chronobiology
  • Bioinformatics
  • Systems Biology

Background:

  • Biological molecules like proteins, mRNA, and metabolites exhibit rhythmic variations, particularly influenced by the day-night cycle.
  • Current bioinformatics tools for rhythm analysis use either single-component harmonic oscillator models for temporal dynamics or multi-component Cosinor models for complex patterns.

Purpose of the Study:

  • To develop a novel bioinformatics platform, PyCycleBio, that integrates the strengths of harmonic oscillator and Cosinor models.
  • To enhance the analysis of biological rhythms by modeling diverse rhythmic behaviors and temporal dynamics.

Main Methods:

  • PyCycleBio employs bounded-multi-component models and modulus operators combined with the harmonic oscillator equation.
  • The platform models rhythmic behaviors, including temporal dynamics regulation through amplitude coefficients.

Main Results:

  • PyCycleBio demonstrates superior sensitivity and functionality compared to existing analytical frameworks.
  • The platform reveals novel associations between data types (transcriptomics, proteomics, metabolomics), sampling conditions, and rhythmic characteristics.
  • New insights into the temporal regulation of biomolecules were uncovered.

Conclusions:

  • PyCycleBio offers an advanced approach for analyzing complex temporal regulation of biomolecules.
  • This platform is expected to significantly advance the field of chronobiology and physiological understanding.
  • The tool is accessible via GitHub, PyPI, and Google Colab for broad usability.