From Data to Models: Analyzing and Integrating Biological Data into Mechanistic Models

Welcome to the GitHub repository for the PhD Course: From Data to Models. This course introduces participants to mechanistic modeling in biology, emphasizing how to analyze and integrate real experimental data into computational models. Through lectures and hands-on sessions, students will work with tools such as Petri Nets, epimod, and Flux Balance Analysis (FBA).

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Course Structure

The repository is organized into four folders:

• Day1: Introduction to mechanistic modeling, Petri Nets, and the epimod framework
• Day2: Model calibration, prediction, and senstivity analysis
• Day3: Working with experimental data and defining models
• Day4: FBA, Data integration and advanced modeling strategies

Each folder includes:

• Slides
• Scripts
• Hands-on examples and datasets

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Required Tools

To run the examples and participate in the hands-on activities, the following tools are required.

Note: Docker and R are already installed on the HPC servers provided for the course. Local installation is optional.

1. GreatSPN

Graphical tool for drawing and simulating Petri Nets.
Installation instructions and downloads are available at:
greatspnHOWTOINSTALL

2. Docker

Docker is required to run the epimod framework via containerized images.
Follow the installation guide here: https://docs.docker.com/get-docker/

After installation, enable non-root access to Docker with:

sudo groupadd docker      # Create the docker group (if not already present)
sudo usermod -aG docker $USER

3. R, RStudio, and epimod (optional for local execution)

These are not required if you are using the HPC servers provided during the course.

To set up locally:

Install R and RStudio.

Install required packages in R:

install.packages("remotes")
install.packages("fdatest")
remotes::install_github('qBioTurin/epimod', ref='epimod_pFBA', dependencies=TRUE)

library(epimod)
downloadContainers()  # Downloads all necessary Docker images

4. ORCA

https://github.com/qBioTurin/ORCA