Scaling Gene Regulatory Networks Simulations¶

Prerequisites¶

By the end of this workshop, participants should be able to:

explain the concept of modelling and simulations, and how simulations can help answer research questions;
briefly describe the main steps of gene expression, and explain what is a Gene Regulatory Network;
list several classes of GRN models;
generate a small random GRN with the sismonr package and simulate the expression of its gene;
submit and manage jobs on a cluster using a scheduler and use software through environment modules;
automate a large number of tasks on a HPC using array jobs.

How to :
- construct a mathematical or statistical model for a specific biological system of interest;
- estimate model parameters based on experimental data;
- reconstruct a GRN from experimental data;
Any questions we don't have an answer for 🤦

Before getting started, have a look at the Supplementary data for instructions on how to connect to NeSI Mahuika Jupyter.

Lesson	Overview
1. Introduction	General overview of Simulations , Gene Regulatory Networks and Simulating Gene Regulatory networks
2. Getting started with sismonr	Describe how `sismonr` package works and running the first simulation
3. Scaling up your work	Introduction to High Performance Computing
4. Working with job scheduler	Introduction to HPC Job Schedulers, Slurm Scheduler & life cycle of a Slurm job, Assessing resource utilisation and profiling
5. Parallel job arrays	Introduction to specifications in Parallel Computing, Slurm Job arrays and Exercises on Scaling networks
6. Post-processing	Interpreting `sismonr` output and Visualising the simlulations
Supplementary-material.1
Supplementary-material.2

Day	Time	Topic
1^st day:	10am-12:30pm	1. Introduction
	12:30pm-1:30pm	Lunch break
	1:30pm-2:30pm	2. Getting started with sismonr
	2:30pm-3.30pm	3. Scaling up your work 4. Working with job scheduler
2^nd day:	10am-12pm	5. Automating large number of tasks
	12pm-1pm	Lunch break
	1pm-2.30pm	5. Post-processing
	2.30pm -	Question time