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Introduction to In Silico Modeling to Study ROS Dynamics.

Jana Schleicher1

  • 1Experimental Transplantation Surgery, Department of General, Visceral and Vascular Surgery, University Hospital Jena, Jena, Germany. janaschleicher@gmail.com.

Methods in Molecular Biology (Clifton, N.J.)
|August 29, 2020
PubMed
Summary

This guide introduces computational modeling for biologists new to the field. It provides a tutorial for building simple models of reactive oxygen species (ROS) dynamics without extensive programming knowledge.

Keywords:
Agent-based modelsComputational modelingMathematical modelsModel development processesOrdinary differential equationsROS biology

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Biophysics

Background:

  • Reactive oxygen species (ROS) play crucial roles in cellular signaling and disease.
  • Experimental biologists often lack computational modeling expertise.
  • Bridging this gap is essential for advancing ROS research.

Purpose of the Study:

  • To introduce computational modeling concepts to biologists experienced in ROS.
  • To provide a practical tutorial for simulating ROS dynamics.
  • To empower biologists to build their own basic computational models.

Main Methods:

  • Introduction to computational modeling principles.
  • Overview of beginner-friendly modeling software.
  • Step-by-step tutorial for developing equation-based ROS models.
  • Discussion of common pitfalls and limitations.

Main Results:

  • Biologists can gain foundational modeling skills without advanced programming.
  • Simple equation-based models of ROS dynamics are achievable for newcomers.
  • Understanding model development processes is facilitated through a practical tutorial.

Conclusions:

  • Computational modeling offers valuable insights into ROS biology.
  • This chapter equips biologists with the necessary skills to start building their own models.
  • Further learning resources are provided to enhance modeling capabilities.