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

Participants will learn via a mix of pre-recorded lectures, live presentations, and trainer Q&A sessions. Practical experience will be developed through group activities and trainer-led computational exercises. Live sessions will be delivered using Zoom with additional support and asynchronous communication via Slack.

Pre-recorded material may be provided before the course starts that participants will need to watch, read, or work through to gain the most out of the actual training event. 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.

Participants will need to be available between the hours of 09:00 – 17:30 GMT each day of the course. Trainers will be available to assist, answer questions, and provide further explanations during these times.

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 you 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
• Model curation through practical experience in a group challenge

Trainers

How to apply tab

Please read our support page before starting your application. In order to be considered for a place on this course, you must do the following:

• Complete the online application form.
• Ensure you add relevant information to the ‘submission details’ section where you are asked to provide information on your:
  • pre-requisite skills and knowledge
  • current work and course expectations
  • data availability
• Upload one letter of support from your supervisor or a senior colleague detailing reasons why you should be selected for the course.

Please submit all documents during the application process by 23:59 on 6 December 2023. Items marked * in the application are mandatory. Incomplete registrations will not be processed. 

All applicants will be informed of the status of their application (successful, waiting list, unsuccessful) by 14 December 2023. If you have any questions regarding the application process please contact Juanita Riveros. 

The registration fee of £225.00 includes:

• access to the full five-day course programme
• access to a bespoke online course handbook
• secure community space on Slack
• virtual machine to work on that is accessed via the internet
• dedicated online support team
• course certificate on completion of the course
   

Course materials

The course materials from the 2022 edition of the course are now live and available for you to use. They provide a mixture of pre-recorded lectures, presentations, and practicals from the course, and will give you a snapshot of what to expect in the 2024 edition.

Flash talks

All participants will be asked to give a short presentation about their research work as part of the course. These provide an opportunity to share their research with the other participants and provide a forum for discussion. Successful applicants will be required to submit their talks upon registration.

Posters

All participants are expected to present a poster that will be shared via the course handbook and other virtual platforms used for the course. Successful applicants will be asked to submit their poster upon registration. 

All posters should:

• Be a .png or .jpg file
• Use a 16:9 aspect ratio:
  • Landscape is preferable but portrait can be used.
  • You can use PowerPoint, Canva, or another third-party application to design and save a 16:9 image.
  • Have a maximum file size of 3 MB.
• Not use a transparent background.

We expect the posters to act as a talking point between you, other participants and the trainers on the course. The posters can be viewed before and during the course, so people can view them during breaks and lunch. They should give the reader an idea of the work you are engaged in, what you are planning to do next, and anything of interest that might be useful for sharing with other participants.