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Related Concept Videos

Relative Velocity in One Dimension01:10

Relative Velocity in One Dimension

The understanding of the concept of reference frames is essential to discuss relative motion in one or more dimensions. When we say that an object has a certain velocity, we must state the velocity with respect to a given reference frame. In most examples, this reference frame has been Earth. For instance, if a statement reads that a person is sitting in a train moving at 10 m/s east, then it implies that the person on the train is moving relative to the surface of Earth at this velocity,...
Relative Motion Analysis - Velocity01:24

Relative Motion Analysis - Velocity

A stroke engine has a slider-crank mechanism that converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider.
When an external force is exerted, it sets the crank into a rotational movement. This, in turn, instigates the motion of the connecting rod, leading to what is referred to as a general plane motion. This process involves two key points - point A on the connecting rod...
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

The motion of molecules in a gas is random in magnitude and direction for individual molecules, but a gas of many molecules has a predictable distribution of molecular speeds. This predictable distribution of molecular speeds is known as the Maxwell-Boltzmann distribution. The distribution of molecular speeds in liquids is comparable to that of gases but not identical and can help to understand the phenomenon of the boiling and vapor pressure of a liquid. Consider that a molecule requires a...
Relative Velocity in Two Dimensions01:11

Relative Velocity in Two Dimensions

Relative velocity is the velocity of an object as observed from a particular reference frame, or the velocity of one reference frame with respect to another reference frame. The concept of relative velocity can be used to describe motion in two dimensions. Consider a particle P and two reference frames S and S′. The position of the origin of S′ as measured in S is , the position of P as measured in S′ is , and the position of P as measured in S is , which can be evaluated by utilizing vector...
Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

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...

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Related Experiment Video

Updated: Jun 7, 2026

A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA
12:05

A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA

Published on: October 1, 2017

ArchVelo: archetypal velocity modeling for single-cell multi-omic trajectories.

Maria Avdeeva1, Sarah K Walker2, Joris van der Veeken3

  • 1Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, New York, NY, USA. mavdeeva@flatironinstitute.org.

Nature Communications
|June 5, 2026
PubMed
Summary

ArchVelo models gene regulation and cellular dynamics using single-cell multi-omic data. This computational framework accurately infers cell differentiation trajectories and identifies key regulatory factors for immune cells.

Related Experiment Videos

Last Updated: Jun 7, 2026

A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA
12:05

A Simple, Robust, and High Throughput Single Molecule Flow Stretching Assay Implementation for Studying Transport of Molecules Along DNA

Published on: October 1, 2017

Area of Science:

  • Genomics and Computational Biology
  • Single-cell Multi-omics Analysis
  • Systems Biology

Background:

  • Inferring dynamic cellular processes from static single-cell genomics data is a significant challenge.
  • Understanding gene regulation and cell fate decisions requires integrating different molecular layers.
  • Existing computational methods often struggle with accuracy in trajectory inference and latent time alignment.

Purpose of the Study:

  • To introduce ArchVelo, a novel computational framework for modeling gene regulation and inferring cellular trajectories.
  • To leverage paired single-cell chromatin accessibility (scATAC-seq) and transcriptomic (scRNA-seq) data for dynamic modeling.
  • To identify regulatory programs (archetypes) and their influence on transcription and cell differentiation.

Main Methods:

  • Developed ArchVelo, a framework representing chromatin accessibility as archetypes (shared regulatory programs).
  • Modeled the dynamic influence of archetypes on gene transcription.
  • Benchmarked ArchVelo on mouse brain and human hematopoiesis datasets, comparing trajectory inference accuracy and latent time alignment.

Main Results:

  • ArchVelo demonstrated superior performance in trajectory inference accuracy and gene-level latent time alignment compared to existing methods.
  • The framework enabled trajectory decomposition into archetypal components and identification of underlying transcription factors.
  • Applied to CD8 T cells in viral infection, ArchVelo revealed distinct differentiation and proliferation trajectories, including progenitor exhausted CD8 T cells.

Conclusions:

  • ArchVelo provides a principled and accurate framework for modeling dynamic gene regulation from multi-omic single-cell data.
  • The method successfully infers cellular trajectories and regulatory mechanisms, particularly in immune cell differentiation.
  • ArchVelo offers valuable insights into sustained immunity and immunotherapy response by characterizing progenitor exhausted CD8 T cell differentiation.