Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Improving Translational Accuracy

Improving Translational Accuracy

Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

Cooperative Allosteric Transitions

Cooperative Allosteric Transitions

Cooperative Allosteric Transitions

Cooperative Allosteric Transitions

Noncovalent Attractions in Biomolecules

Noncovalent Attractions in Biomolecules

Epistasis Analysis

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...

You might also read

Related Articles

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

Sort by

Same author

An Entropy-Based Framework for Hybrid Coalitions in Game Theory-Part I: Human Arbitration.

Entropy (Basel, Switzerland)·2026

Same author

Entropic and algebraic transcript-based tools in time series analysis.

Chaos (Woodbury, N.Y.)·2026

Same author

Introduction to Focus Issue: Nonautonomous dynamical systems: Theory, methods, and applications.

Chaos (Woodbury, N.Y.)·2026

Same author

Noise Robustness of Transcript-Based Estimators for Properties of Interactions.

Entropy (Basel, Switzerland)·2025

Same author

Permutation-Based Distances for Groups and Group-Valued Time Series.

Entropy (Basel, Switzerland)·2025

Same author

Functional Importance Backbones of the Brain at Rest, Wakefulness, and Sleep.

Brain sciences·2025

Same journal

Gap junction architecture and synchronization clusters in the thalamic reticular nuclei.

Chaos (Woodbury, N.Y.)·2026

Same journal

Exact computation of Lyapunov exponents via system parameters in multi-triangle chaotic maps: Bifurcation analysis and circuit realization.

Chaos (Woodbury, N.Y.)·2026

Same journal

Integrating score-based generative modeling and neural ODEs for accurate representation of multiscale chaotic dynamics.

Chaos (Woodbury, N.Y.)·2026

Same journal

A data-driven tuberculosis model with behavioral changes and saturated treatment: Optimal control and cost-effectiveness study.

Chaos (Woodbury, N.Y.)·2026

Same journal

Breathers, rational solutions, and their exact physical spectra in F = 1 spinor Bose-Einstein condensates.

Chaos (Woodbury, N.Y.)·2026

Same journal

Finite invariant sets with bridging points in logistic IFS.

Chaos (Woodbury, N.Y.)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 7, 2026

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets

Published on: February 23, 2024

Transcript-based estimators for characterizing interactions.

Manuel Adams¹, José M Amigó², Klaus Lehnertz^1,3,4

¹Department of Epileptology, University of Bonn Medical Centre, Venusberg Campus 1, Bonn 53127, Germany.

Chaos (Woodbury, N.Y.)

|January 2, 2026

Summary

This summary is machine-generated.

This study revives the transcript concept for analyzing time series interactions. Transcript-based methods reveal complex spatial-temporal brain dynamics across different human vigilance states.

More Related Videos

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Published on: December 1, 2023

Related Experiment Videos

Last Updated: Jan 7, 2026

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets

Published on: February 23, 2024

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Published on: December 1, 2023

Area of Science:

Complex Systems Analysis
Neuroscience
Time Series Analysis

Background:

The concept of transcripts, introduced in 2009, provides a framework for characterizing functional relationships between interacting time series using algebraic relations between ordinal patterns.
Estimators for interaction strength, direction, and complexity based on transcripts have been developed but lack widespread application in real-world system studies.

Purpose of the Study:

To revisit the transcript concept and demonstrate the utility of transcript-based estimators for investigating interactions in dynamical systems.
To apply these methods to analyze human brain dynamics and uncover insights into spatial-temporal interactions related to vigilance states.

Main Methods:

Utilized transcript-based estimators derived from algebraic relations between ordinal patterns of time series.
Performed time-resolved analysis on multichannel, multiday recordings of human brain activity.
Investigated interactions in coupled paradigmatic dynamical systems of varying complexity.

Main Results:

Successfully applied transcript-based estimators to analyze complex interactions in dynamical systems.
Demonstrated the potential of these methods for time-series-based investigation of real-world systems.
Revealed novel insights into intricate spatial-temporal interactions in human brain dynamics during different vigilance states.

Conclusions:

Transcript-based methods offer a powerful approach for characterizing functional relationships and interactions in complex systems.
The application to human brain dynamics highlights the potential for novel discoveries in neuroscience.
This work encourages wider adoption of transcript-based estimators in diverse scientific fields.