Competency framework

PerMedCoE has created a competency framework to define the abilities required by professionals in the field of computational personalised medicine. The framework constitutes the basis of our training programme, where the courses will be aimed at covering components of the defined competencies. In addition, the framework includes career profiles, which represent professionals with different roles in the field and list the competencies needed in those roles. You can explore the available profiles and create your own to find out which competencies you need to develop further. We provide a list of training resources associated with the competencies, which you can use to develop the competencies that are relevant for you. You can browse through the PerMedCoE competency framework on the EMBL-EBI Competency Hub: https://competency.ebi.ac.uk/

 

 

On this page, we provide a list of PerMedCoE training activities and materials together with the competencies that they contribute to develop.

Training resource  Associated competencies

Introduction to HPC for life 

scientists

  • Operate effectively within a Linux environment
  • Use a batch job system
  • Monitor application execution
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem)

Course on HPC-based 

computational biomedicine

  • Apply expertise in medical or biomedical sciences – Operate effectively within a Linux environment – Use a batch job system
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem)
Drug studies in signalling pathways models and their integration into multiscale models
  • Follow the scientific method and proceed with all the steps in the process of solving a scientific problem
  • Apply expertise in formal, natural and life sciences – Handle data from end to end following best practice
  • Apply data science expertise to clinical and life sciences problems
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem) – Write or adapt scripts and computer programs (software development) to perform simulations in compliance with good programming practice Use a batch job system

Systematising complex and 

combined metabolic analyses with COBREXA.jl

  • Follow the scientific method and proceed with all the steps in the process of solving a scientific problem
  • Apply expertise in formal, natural and life sciences – Handle data from end to end following best practice
  • Apply data science expertise to clinical and life sciences problems
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem) – Write or adapt scripts and computer programs (software development) to perform simulations in compliance with good programming practice

From transcriptomics to 

mechanistic models of signalling

  • Follow the scientific method and proceed with all the steps in the process of solving a scientific problem
  • Apply expertise in formal, natural and life sciences – Handle data from end to end following best practice
  • Apply data science expertise to clinical and life sciences problems
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem) – Write or adapt scripts and computer programs (software development) to perform simulations in compliance with good programming practice

PerMedCoE summer school: from pathway modelling tools to 

cell-level simulations

  • Follow the scientific method and proceed with all the steps in the process of solving a scientific problem
  • Apply expertise in formal, natural and life sciences – Handle data from end to end following best practice
  • Apply data science expertise to clinical and life sciences problems
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem) – Write or adapt scripts and computer programs (software development) to perform simulations in compliance with good programming practice
  • Use a batch job system
  • Use computational workflow systems, understanding their potential benefits and limitations
Training materials on MaBoSS Tutorials on COBREXA 
  • Follow the scientific method and proceed with all the steps in the process of solving a scientific problem
  • Apply expertise in formal, natural and life sciences – Handle data from end to end following best practice
  • Apply data science expertise to clinical and life sciences problems
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem) – Write or adapt scripts and computer programs (software development) to perform simulations in compliance with good programming practice
  • Follow the scientific method and proceed with all the steps in the process of solving a scientific problem
  • Apply expertise in formal, natural and life sciences – Handle data from end to end following best practice
  • Apply data science expertise to clinical and life sciences problems
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem)
  • Write or adapt scripts and computer programs (software development) to perform simulations in compliance with good programming practice
Tutorial on CellNOpt 
  • Follow the scientific method and proceed with all the steps in the process of solving a scientific problem
  • Apply expertise in formal, natural and life sciences – Handle data from end to end following best practice
  • Apply data science expertise to clinical and life sciences problems
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem)
Tutorial on CellNOpt 
  • Follow the scientific method and proceed with all the steps in the process of solving a scientific problem
  • Apply expertise in formal, natural and life sciences – Handle data from end to end following best practice
  • Apply data science expertise to clinical and life sciences problems Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem)
  • Write or adapt scripts and computer programs (software development) to perform simulations in compliance with good programming practice
Tutorial on CARNIVAL 
  • Follow the scientific method and proceed with all the steps in the process of solving a scientific problem
  • Apply expertise in formal, natural and life sciences – Handle data from end to end following best practice
  • Apply data science expertise to clinical and life sciences problems
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem) – Write or adapt scripts and computer programs (software development) to perform simulations in compliance with good programming practice

Tutorial on how to develop Building blocks using the ‘permedcoe’ package 

Working with computing clusters: information and resources 

Tutorial on working with 

computing clusters

  • Package and distribute software
  • Use computational workflow systems, understanding their potential benefits and limitations
  • Use a batch job system
  • Monitor application execution
  • Use a batch job system
Introductory tutorial on using MPI with containers
  • Package and distribute software
  • Write parallel programs

Alternative option 

Introduction to HPC for life scientists 

This resource provides learning to support the development of the following competencies: 

  • Operate effectively within a Linux environment
  • Use a batch job system
  • Monitor application execution
  • Evaluate the ability of a program running in a specific computing environment to perform a simulation (e.g. define algorithmic time and hardware resources required to solve a problem)