Virtual course

Mathematics of life: modelling molecular mechanisms

This course will provide participants with an introduction and hands-on training on modelling approaches, tools and resources used in systems biology as well as touch on network analysis.

Computer models are increasingly used to understand the essential processes of biology. Researchers in academic institutions as well as the pharmaceutical industry use mathematical models to generate hypotheses on how complex biomolecular systems work. Modelling of biochemical pathways deregulated in disease conditions can offer mechanistic insights into the pathology, help to elucidate mechanisms behind drug action, and predict the dose required for treatment thus facilitating fundamental research and drug discovery. This course will provide a helpful brief introduction to key modelling concepts and hands on training to use popular tools and resources used in this scientific field.

Virtual course

This course has now been moved to a virtual format. We will be using Zoom to run the live sessions (all fully password protected with automated English closed captioning and transcription) with support and both scientific and social networking opportunities provided by Slack and other methods, taking different time zones into account. In order to make the most out of the course, you should make sure to have a stable internet connection throughout the week and are available between 09:00 - 17:30 British Summer Time (BST) each day. In the week before the course there will be a brief induction session. Computational practicals will run on EMBL-EBI's virtual training infrastructure, meaning participants will not require access to a powerful computer or install complex software on their own machines.

Who is this course for?

This course is aimed at experimental biologists, bioinformaticians and mathematicians who have just started in systems biology, are familiar with the basic terminology in this field and who are now keen on gaining a better knowledge of systems biology modelling approaches to understand biological and biomedical problems.

An experience of using a programming language (e.g Python, R, Matlab) would be a benefit but is not mandatory.

An undergraduate knowledge of molecular and cellular biology or some background in mathematics is highly beneficial.

What will I learn?

Learning outcomes

After the course, participants should be able to:

  • Identify the strength and weakness of systems qualitative and quantitative modelling approaches
  • Access, query and retrieve data/ models from public repositories for systems biology modelling
  • Use modelling software to develop reproducible systems biology models
  • Discuss the real-life application of models in fundamental and industrial research

Course content

During this course you will learn about: 

  • Network Analysis and Pathway Enrichment
  • Qualitative (e.g. logic) modelling and quantitative (e.g. chemical kinetics, constraint based, statistical) modelling
  • Data resources for modelling, pathways and molecular interaction: BioModels, Reactome, IntAct, ComplexPortal etc.
  • Model sharing: how to encode, annotate and distribute models
  • Several tools will be used during the course, including accessing IntAct data from Cytoscape, COPASI, CompuCell3D and CellCollective
  • Group challenge on model curation

Trainers

Alfonso Arias Martinez
Universidad Pompeu Fabra
Andreas Dräger
University of Tübingen
Anwesha Chaudhury
Novartis
Artem Lomakin
DKFZ
Carmen Pin
Astra Zeneca
Eliot Ragueneau
EMBL-EBI
James Glazier
Indiana University Bloomington
Kalpana Panneerselvam
EMBL-EBI
Krishna Tiwari
EMBL-EBI
Maria Zimmermann-Kogadeeva
EMBL
Rahuman Sheriff
EMBL-EBI
Tomas Helikar
University of Nebraska-Lincoln
This course has ended

12 - 16 September 2022
Online
£200
Contact
Juanita Riveros

Organisers
  • Rahuman Sheriff
    EMBL-EBI
  • Alexandra Holinski
    EMBL-EBI

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