SEGMEnT_HPC

SEGMEnT_HPC performs cell-for-cell anatomic-scale simulations of intestinal pathophysiology using high-performance computing (HPC) and histological data to integrate gut epithelial and organ-level mechanisms.


Key Features:

  • High-performance computing (HPC): Uses HPC resources to enable large-scale anatomic simulations.
  • Massively parallel computation: Employs massively parallel computation to scale simulations to anatomic domains.
  • Cell-for-cell anatomic-scale simulation: Simulates individual cells across whole-anatomic structures of the intestinal tract.
  • SEGMEnT model extension: Extends the SEGMEnT gut epithelium simulation model to anatomic scales.
  • Multiscale spatial modeling: Represents pathophysiological processes across microscopic cellular to macroscopic and organ-level spatial scales.
  • Histology-based modeling: Incorporates histological data for representation of disease diagnosis and staging.

Scientific Applications:

  • Ileal pouchitis simulation: Simulates the pathogenesis and abnormal tissue structures of ileal pouchitis in patients post-surgery for ulcerative colitis.
  • Intestinal tract pathophysiology: Models complex intestinal pathophysiological processes to inform diagnosis and therapeutic strategies.
  • Organ-level disease representation: Represents organ-level structural changes that emerge from cellular abnormalities.

Methodology:

Extends the SEGMEnT gut epithelium model via massively parallel computation on high-performance computing (HPC) systems to perform cell-for-cell anatomic-scale simulations across multiple spatial scales.

Topics

Collections

Details

Tool Type:
command-line tool
Operating Systems:
Linux
Programming Languages:
C++
Added:
4/25/2022
Last Updated:
11/24/2024

Operations

Publications

Cockrell RC, Christley S, Chang E, An G. Towards Anatomic Scale Agent-Based Modeling with a Massively Parallel Spatially Explicit General-Purpose Model of Enteric Tissue (SEGMEnT_HPC). PLOS ONE. 2015;10(3):e0122192. doi:10.1371/journal.pone.0122192. PMID:25806784. PMCID:PMC4373890.