In this section you can find self-learning training materials developed by PerMedCoE technical experts
The PerMedCoE summer school: from pathway modelling tools to cell-level simulations, ran in June 2023 and the materials were made freely available afterwards, including tutorials on PerMedCoE tools, workflows and introduction to HPC.
transcriptutorial: this is a tutorial to guide the analysis of RNAseq dataset using footprint based tools such as DOROTHEA, PROGENY and CARNIVAL.
From transcriptomics to mechanistic models of signalling: this is the Google Colab notebook of the virtual course that ran in April 2023. You will learn how to process differential gene expression data to estimate transcription factor activities with Decoupler, obtain and process PKNs with OmniPath and pypath, and use CARNIVAL through CORNETO to infer signalling networks that explain the activity patterns.
COBREXA.jl provides tutorials and notebooks with the purpose of explaining the most important concepts and functions for metabolic modelling and model handling to users, and then practicing them.
The documentation contains a quick start guide, examples and tutorials that explain the use of analysis methods to solve common tasks, and a guide for running the analyses on a HPC that describes the functionality required for parallel execution of large analyses
This tutorial aims to be an introduction to
i) the preparation of the Prior knowledge network (PKN) of signaling pathways and
ii) the training of the PKN against biochemical data to create cell-specific models.
In the following links you can find more resources to learn about the PerMedCoE tools:
CARNIVAL: a bioinformatics tool that automatically creates signalling networks that explain gene expression data
CellNOpt: a method to derive a logic-based model from a prior knowledge network (PKN) and train it against perturbation measurements
COBREXA: a package for COnstraint Based Reconstruction and EXascale Analysis, designed for researchers interested in metabolic modelling
MaBoSS: a software for simulating signalling and regulatory networks, which produces trajectories describing the evolution of the states’ probabilities of a Boolean model
PhysiCell: a multi-scale agent-based framework for modelling and simulating multicellular systems
PhysiBoSS: an add-on of PhysiCell which enables simulating intracellular signalling and regulatory models inside individual the cell-agents
Here we share part of the material from the course ‘Introduction to HPC for Life Scientists‘, including lectures and practical tutorials about HPC and how to make an efficient use of HPC environments for research in the Life Sciences.
Computational layers. Lecture about software layers in modern computers and HPC environments.
Parallel and distributed computing with PhysiCell. In this practical session, we will explore PhysiCell’s capabilities to run simulations in parallel. In particular, we will take advantage of the different cores that a single machine could have, and subsequently, the different nodes available at a supercomputer such as MareNostrum 4.
Mapping computation to HPC hardware & GPU accelerators and heterogeneous architectures. Lectures and exercises about:
- Mapping computation to HPC hardware: molecular simulation
- GPU accelerators and heterogeneous architectures
- Introduction to HPC: molecular dynamics simulations with GROMACS
This section provides a step-by-step by tutorial on how to develop Building Blocks using the permedcoe package and an application that uses them.
This page collects together general information and resources for working with different computing clusters hosted by HPC centres and universities affiliated with PerMedCoE.
This tutorial provides an introduction to how to access a computing cluster, manage your data and submit jobs using a batch job system.
In this material we will briefly touch upon why MPI is such a tricky component, explain the main approaches to combine MPI with containers and discuss when it is actually worthwhile to use MPI containers.