Jove
Visualize
Contact Us

Related Concept Videos

T Cell Activation and Clonal Selection01:22

T Cell Activation and Clonal Selection

16.2K
T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...
16.2K
Hematopoiesis01:21

Hematopoiesis

9.1K
The process of blood cell formation is called hematopoiesis. Hematopoiesis starts early during development, on the seventh day of embryogenesis. This phase of hematopoiesis is called the primitive wave, wherein the extraembryonic yolk sac allows the production of erythroid cells and endothelial cells from a common precursor called hemangioblast. The erythroid cells provide oxygen to support the growth of the rapidly dividing embryo. Hemangioblasts later develop into hematopoietic stem cells or...
9.1K
Overview of Hematopoiesis01:20

Overview of Hematopoiesis

9.7K
Hematopoiesis, or blood cell production, is a vital biological process that begins early in embryonic development and continues throughout life. This process generates the various types of cells found in blood, including red blood cells, white blood cells, and platelets from hematopoietic stem cells (HSCs).
Developmental Phases of Hematopoiesis
Initially, HSCs are formed in the embryonic yolk sac, a critical site for early blood cell production. These stem cells subsequently migrate to other...
9.7K
Mutations01:39

Mutations

94.6K
Overview
94.6K
Approximate Integration01:24

Approximate Integration

58
In many practical and theoretical contexts, the exact value of a definite integral may be inaccessible. This limitation typically arises when the antiderivative of a function is either unknown or cannot be expressed in a closed mathematical form. Alternatively, it can occur when a function is defined not by a formula but by a finite set of empirical data points, such as those collected during experiments. In these cases, approximate integration techniques provide a valuable solution.One of the...
58
Diffusion01:12

Diffusion

221.0K
Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
221.0K

You might also read

Related Articles

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

Sort by
Same author

Accurate detection of tumor clonality and ongoing expansion mode from genomic data.

bioRxiv : the preprint server for biology·2026
Same author

Scalable subclonal reconstruction of cancer cells in DNA sequencing data using a penalized likelihood model.

bioRxiv : the preprint server for biology·2026
Same author

Predicting glioma survival and extracellular matrix remodeling through MRI radiogenomics.

Cell reports. Medicine·2026
Same author

Delta radiomics-based nomogram for preoperative prediction vessels encapsulating tumor clusters (VETC) and prognosis in hepatocellular carcinoma using dynamic contrast-enhanced CT.

BMC medical imaging·2026
Same author

Enhancing preoperative HER2 status classification of invasive breast cancers using machine learning models based on clinicopathological and MRI features: a multicenter study.

Frontiers in cell and developmental biology·2025
Same author

Statistical and Evolutionary Analysis of Sequenced DNA from Breast Cancer FFPE Specimens.

bioRxiv : the preprint server for biology·2025
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 Experiment Video

Updated: Feb 10, 2026

Bone Marrow Transplantation Procedures in Mice to Study Clonal Hematopoiesis
08:00

Bone Marrow Transplantation Procedures in Mice to Study Clonal Hematopoiesis

Published on: May 26, 2021

14.2K

BESTish: A Diffusion-Approximation Framework for Inferring Selection and Mutation in Clonal Hematopoiesis.

Ren-Yi Wang1,2, Khanh N Dinh2, Keito Taketomi2,3

  • 1Department of Statistics, Rice University, Houston, TX, USA.

Biorxiv : the Preprint Server for Biology
|February 9, 2026
PubMed
Summary

Clonal hematopoiesis (CH) involves mutant stem cell expansion. We developed BESTish, a Bayesian method to model CH evolution and analyze variant allele frequency (VAF) dynamics, revealing patient-specific mutation behaviors.

More Related Videos

Characterizing Mutational Load and Clonal Composition of Human Blood
07:58

Characterizing Mutational Load and Clonal Composition of Human Blood

Published on: July 11, 2019

7.9K
The Lambda Select cII Mutation Detection System
07:08

The Lambda Select cII Mutation Detection System

Published on: April 26, 2018

8.4K

Related Experiment Videos

Last Updated: Feb 10, 2026

Bone Marrow Transplantation Procedures in Mice to Study Clonal Hematopoiesis
08:00

Bone Marrow Transplantation Procedures in Mice to Study Clonal Hematopoiesis

Published on: May 26, 2021

14.2K
Characterizing Mutational Load and Clonal Composition of Human Blood
07:58

Characterizing Mutational Load and Clonal Composition of Human Blood

Published on: July 11, 2019

7.9K
The Lambda Select cII Mutation Detection System
07:08

The Lambda Select cII Mutation Detection System

Published on: April 26, 2018

8.4K

Area of Science:

  • Hematology
  • Computational Biology
  • Genetics

Background:

  • Clonal hematopoiesis (CH) is driven by somatic mutations in hematopoietic stem cells (HSCs).
  • Understanding CH evolution requires accurate modeling of variant allele frequency (VAF) dynamics.
  • Environmental factors can influence HSC fitness and clonal expansion.

Purpose of the Study:

  • To develop a novel stochastic model for analyzing CH trajectories.
  • To create an efficient and accurate Bayesian inference method (BESTish) for CH driver analysis.
  • To quantify mutation fitness, rate, and environmental effects in CH.

Main Methods:

  • Developed a state-dependent stochastic model of wild-type and mutant HSCs.
  • Derived mean-field dynamics and Gaussian-Markov approximation for VAF.
  • Introduced BESTish, a Bayesian inference method using closed-form distributions for VAF data.

Main Results:

  • Mean VAF trajectory follows a logistic form influenced by selective advantage.
  • Environmental factors impact VAF variance and autocovariance, not the mean trajectory.
  • BESTish provides consistent mutation fitness and rate estimates across studies.
  • Identified patient-specific heterogeneity in mutation selection and non-homeostatic environments.

Conclusions:

  • BESTish offers a unified framework for quantifying CH evolution.
  • The method accurately estimates key parameters like mutation fitness and environmental strength.
  • Reveals patient-specific clonal dynamics and identifies mutations in growth-facilitating environments.