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

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

27
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
27
Synthetic Biology02:55

Synthetic Biology

4.7K
Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
4.7K
Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

2.1K
Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
2.1K
Adaptability of Cytoskeletal Filaments01:12

Adaptability of Cytoskeletal Filaments

3.7K
The cytoskeleton is a complex dynamic structure performing varied functions based on cellular requirements. The adaptability of the individual filaments in the cytoskeleton determines their ability to perform various functions within the cell. It can undergo rapid reorganization during processes like cell division or remain stable for several hours as in the interphase. The adaptability of these filaments depends on stringent regulatory mechanisms. The microfilament and microtubules of the...
3.7K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

40
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
40
Two-Dimensional Microscopy in Microbiology01:29

Two-Dimensional Microscopy in Microbiology

1
Two-dimensional (2D) microscopy encompasses a range of optical techniques that capture images within a single focal plane, offering detailed representations of microscopic structures. These techniques are essential in biological and medical research, enabling the visualization of cellular and subcellular structures with different levels of contrast and specificity.There are several major types of 2D microscopy, each with strengths and applications.Bright-Field MicroscopyBright-field microscopy...
1

You might also read

Related Articles

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

Sort by
Same author

Combinatorial decision-making driven by multicomponent surface condensates.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Minimizing co-growth as a broad predictor of community robustness.

bioRxiv : the preprint server for biology·2026
Same author

Simple biological controllers drive the evolution of soft modes.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Unifying theories in high-dimensional biophysics: approaches, challenges and opportunities.

NPJ systems biology and applications·2026
Same author

Evolution of error correction through a need for speed.

Science (New York, N.Y.)·2026
Same author

Theoretical limits for sensing through phase separation.

Proceedings of the National Academy of Sciences of the United States of America·2026

Related Experiment Video

Updated: Jun 3, 2025

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.1K

Soft Modes as a Predictive Framework for Low Dimensional Biological Systems across Scales.

Christopher Joel Russo1,2, Kabir Husain1,3, Arvind Murugan1,4

  • 1James Franck Institute, University of Chicago, Chicago, United States.

Arxiv
|January 7, 2025
PubMed
Summary

Biological systems exhibit surprisingly simple responses to disturbances, explained by a unifying "soft modes" framework. This approach generalizes concepts across biology, from molecules to ecosystems, and predicts phenomena like phenocopying.

Keywords:
bufferingdimensionality reductionepistasisphenocopyingslow modessoft modes

More Related Videos

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.1K
Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

3.1K

Related Experiment Videos

Last Updated: Jun 3, 2025

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.1K
JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.1K
Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

3.1K

Area of Science:

  • Biology
  • Dynamical Systems Theory
  • Systems Biology

Background:

  • Biological systems face constant perturbations from various sources.
  • Despite complexity, biological responses are often low-dimensional and stereotyped.
  • Existing models struggle to unify these observations across different biological scales.

Purpose of the Study:

  • To introduce and explore the unifying dynamical systems framework of "soft modes".
  • To explain and analyze the observed low-dimensionality in biological system responses.
  • To demonstrate how soft modes generalize classic biological concepts to diverse systems.

Main Methods:

  • Utilizing a dynamical systems framework centered on "soft modes".
  • Analyzing high-throughput experimental data to identify low-dimensional responses.
  • Developing theoretical predictions based on the soft modes framework.

Main Results:

  • Soft modes provide a unifying explanation for low-dimensional biological responses.
  • The framework makes non-trivial predictions, including phenocopying, dual buffering, and global epistasis.
  • These predictions generalize across biological scales, from molecular to ecological systems.

Conclusions:

  • Soft modes offer a powerful and unifying framework for understanding biological system dynamics.
  • The approach has broad applicability, from protein biophysics to microbial ecology.
  • Further experimental validation of soft mode predictions is warranted across diverse biological fields.