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

You might also read

Related Articles

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

Sort by
Same author

Sequential transcriptional waves and NF-κB-driven chromatin remodeling direct drug-induced dedifferentiation in cancer.

Nature communications·2026
Same author

Cellular heterogeneity and therapeutic response profiling of human IDH + glioma stem cell cultures.

Scientific reports·2025
Same author

Digital twin models for predicting venetoclax and azacitidine-induced neutropenia in patients with acute myeloid leukemia.

NPJ digital medicine·2025
Same author

Cellular heterogeneity and therapeutic response profiling of human IDH+ glioma stem cell cultures.

bioRxiv : the preprint server for biology·2025
Same author

Medical digital twins: enabling precision medicine and medical artificial intelligence.

The Lancet. Digital health·2025
Same author

Classification of non-TCGA cancer samples to TCGA molecular subtypes using compact feature sets.

Cancer cell·2025
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
Same journal

EDEL: Enhancing Dense Retrievers for Curation of Biomedical Knowledge Bases.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Apr 26, 2026

Mechanostimulation of Multicellular Organisms Through a High-Throughput Microfluidic Compression System
09:56

Mechanostimulation of Multicellular Organisms Through a High-Throughput Microfluidic Compression System

Published on: December 23, 2022

1.8K

Biocellion: accelerating computer simulation of multicellular biological system models.

Seunghwa Kang1, Simon Kahan1, Jason McDermott1

  • 1Computational Biology and Bioinformatics Group, High-performance Computing Group, Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology, Seattle, WA 98109, USA.

Bioinformatics (Oxford, England)
|July 28, 2014
PubMed
Summary
This summary is machine-generated.

Biocellion is a new software framework that simplifies the use of high-performance parallel computers for biological system modeling. This enables complex simulations of cellular behaviors without requiring specialized parallel programming expertise.

More Related Videos

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
10:24

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Published on: September 19, 2019

5.5K
In Silico Clinical Trials for Cardiovascular Disease
09:09

In Silico Clinical Trials for Cardiovascular Disease

Published on: May 27, 2022

2.1K

Related Experiment Videos

Last Updated: Apr 26, 2026

Mechanostimulation of Multicellular Organisms Through a High-Throughput Microfluidic Compression System
09:56

Mechanostimulation of Multicellular Organisms Through a High-Throughput Microfluidic Compression System

Published on: December 23, 2022

1.8K
Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
10:24

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Published on: September 19, 2019

5.5K
In Silico Clinical Trials for Cardiovascular Disease
09:09

In Silico Clinical Trials for Cardiovascular Disease

Published on: May 27, 2022

2.1K

Area of Science:

  • Computational Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Biological systems involve complex interactions between cells and their environment.
  • Mathematical modeling and computer simulation are key tools for understanding biological systems.
  • Agent-based modeling is popular but computationally intensive, limiting simulations of large systems.

Purpose of the Study:

  • To develop a high-performance software framework, Biocellion, for biological system modeling.
  • To enable efficient use of parallel computers for complex biological simulations.
  • To reduce the effort required for computational biologists to simulate large-scale biological systems.

Main Methods:

  • Biocellion utilizes a high-performance software framework designed for parallel computers.
  • Users define model specifics by filling in pre-defined model routines.
  • The framework supports a wide range of multicellular biological system models.

Main Results:

  • Biocellion allows modelers without parallel computing expertise to efficiently use parallel computers.
  • Simulations of cell sorting, microbial patterning, and bacterial systems in soil aggregates were successfully performed.
  • The software simplifies the process compared to writing sequential programs from scratch.

Conclusions:

  • Biocellion effectively addresses the computational challenges in modeling large biological systems.
  • The framework democratizes the use of high-performance computing for biological research.
  • Biocellion facilitates more complex and accurate simulations of cellular and multicellular behaviors.