ANISE

ANISE configures TiFoSi mechanobiology simulations by constructing gene regulatory network equations and generating TiFoSi-compatible XML configuration files for studies of mechanical forces and signaling in planar epithelia.


Key Features:

  • Configurator: Constructs complete configuration files for TiFoSi and outputs XML compatible with TiFoSi execution.
  • Equation Builder: Constructs modeling equations for gene regulatory networks and encodes them into the TiFoSi configuration format.
  • Module Coverage: Supports specification of initial conditions, mechanical properties, and signaling pathways for TiFoSi simulations.
  • TiFoSi Integration: Translates user-defined model components and parameters into the XML format required by TiFoSi for simulation execution.

Scientific Applications:

  • Mechanobiology of planar epithelia: Enables simulation of the interplay between mechanical forces and signaling in planar epithelial tissues.
  • Tissue morphogenesis: Supports modeling of processes driving tissue shape and pattern formation.
  • Wound healing simulations: Facilitates in silico studies of cellular responses during tissue repair.
  • Cancer cell migration: Allows simulation of migratory behaviors influenced by mechanical cues and signaling.
  • Hypothesis testing and validation: Produces simulation setups that can be used for computational hypothesis testing and experimental comparison.

Methodology:

Constructs modeling equations for gene regulatory networks, configures TiFoSi modules including initial conditions, mechanical properties, and signaling pathways, and translates these configurations into TiFoSi-compatible XML files.

Topics

Details

License:
Not licensed
Tool Type:
command-line tool, web application
Operating Systems:
Mac, Linux, Windows
Programming Languages:
JavaScript
Added:
9/26/2022
Last Updated:
9/26/2022

Operations

Publications

Rodríguez Cerro Á, Sancho S, Rodríguez M, Gamón MA, Guitou L, Martínez RJ, Buceta J. <i>ANISE</i>: an application to design mechanobiology simulations of planar epithelia. Bioinformatics. 2022;38(17):4246-4247. doi:10.1093/bioinformatics/btac511. PMID:35856714.

PMID: 35856714
Funding: - Spanish Ministry of Science and Innovation: PID2019-105566GB-I00

Documentation

Links