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

Morphogenesis02:19

Morphogenesis

Plant morphogenesis—the development of a plant’s form and structure—involves several overlapping developmental processes, including growth and cell differentiation. Precursor cells differentiate into specific cell types, which are organized into the tissues and organ systems that make up the functional plant.
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Shape and Texture of Coarse Aggregate01:25

Shape and Texture of Coarse Aggregate

Aggregate shape is classified based on the relative sharpness or roundness of the edges and corners. This classification includes categories like rounded, angular, elongated, and flaky, each with specific characteristics. Rounded aggregates, fully shaped by attrition, are typical of river or seashore gravel, while angular aggregates, such as crushed rock, have well-defined edges. Aggregates that are elongated and flaky are less desirable, as they can reduce the workability and strength of...
Modeling and Similitude01:12

Modeling and Similitude

Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...

You might also read

Related Articles

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

Sort by
Same author

Label-Free All-Electrical Tracking of Individual and Collective Cell Migration on a Megapixel CMOS Capacitance Sensor.

bioRxiv : the preprint server for biology·2026
Same author

Evaluating the role of pretraining dataset size and diversity on single-cell foundation model performance.

Nature methods·2026
Same author

Physical contact reveals a hidden layer of cortical architecture.

bioRxiv : the preprint server for biology·2026
Same author

Partial EMT Drives Persistent Collective Migration via Collision Guidance in Heterogeneous Populations.

bioRxiv : the preprint server for biology·2026
Same author

Profiling extracellular matrix-driven heterogeneity of single cell migration and morphology.

Scientific reports·2026
Same author

75 Years of Mathematical Oncology.

bioRxiv : the preprint server for biology·2026

Related Experiment Video

Updated: Jul 13, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

11.8K

Generative modeling of biological shapes and images using a probabilistic -shape sampler.

Emily T Winn-Nuñez1, Hadley Witt2,3, Dhananjay Bhaskar4

  • 1Division of Applied Mathematics, Brown University, Providence, RI, USA.

Biorxiv : the Preprint Server for Biology
|January 23, 2024
PubMed
Summary

We introduce the A-shape sampler, a new probabilistic framework for generating realistic 2D and 3D shapes. This tool aids in understanding morphological variation in computational biology, especially when real data is scarce.

More Related Videos

Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

7.1K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.0K

Related Experiment Videos

Last Updated: Jul 13, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

11.8K
Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

7.1K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.0K

Area of Science:

  • Computational biology
  • Biostatistics
  • Geometric morphometrics

Background:

  • Understanding morphological variation is crucial in computational biology.
  • Current methods for shape analysis often struggle with limited or inaccessible real-world data.
  • Existing generative models for shapes lack systematic assessment capabilities.

Conclusions:

  • The A-shape sampler offers a flexible and powerful approach for modeling morphological variation.
  • This framework addresses limitations in data availability and generative model assessment in shape analysis.
  • The open-source availability promotes wider adoption and further development in computational biology.