Summer School in Bioinformatics

24–28 June 2019

Wellcome Genome Campus, UK

In collaboration with EMBL-EBI


This popular computational course, run jointly with EMBL-EBI, provides an introduction to the use of bioinformatics in biological research.
Participants will gain hands-on training in the tools and resources appropriate to their research.

The programme will focus on bioinformatics theory and practice, including best practices for undertaking bioinformatics analysis, data management and reproducibility. Participants will also take part in a group project to conduct bioinformatics-based research and explore biological questions. The programme includes discussions on the applications of bioinformatics in biological research and practical examples on how to browse, search, and retrieve biological data from public repositories.

The group work will culminate in a presentation session involving all participants on the final day of the course, providing an opportunity for wider discussion on the benefits and challenges of working with biological data. Groups are mentored by the trainers who set the initial challenge, but active participation from all group members is expected.

This course is aimed at individuals working across biological sciences who have little or no experience in bioinformatics. Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their skills and knowledge further. No previous knowledge of programming / coding is required for this course.

Please note:
The course will not cover in-depth data analysis; there will be no opportunity for you to analyse your own data during this course.

Learning outcomes
Following course completion participants should be able to:

  • Discuss applications of bioinformatics in biological research
  • Browse, search, and retrieve biological data from public repositories
  • Use appropriate bioinformatics tools to explore biological data
  • Comprehend some ways biological data can be stored, organised and interconverted


The course will start at approximately 10.00 on Monday, 24 June and close at approximately 15.30 on Friday, 28 June 2019.

This is a residential course. All students are requested to stay onsite for the full duration to benefit fully from discussions and interactions with the faculty and other students.

During this course you will learn about:

  • Bioinformatics as a science
  • Designing bioinformatics studies
  • Data management and reproducibility
  • Basic tools and resources for bioinformatics

Group projects

Participants will be divided into focused groups to work on a small project. In your application you should indicate which of the following
projects would most benefit your research:

Networks and pathways
The project will make use of gene expression data (RNA-seq) to build protein-protein interaction networks which can be used to explore functional relationships between the (potentially) expressed protein products. You will use Cytoscape to visualise protein networks, identify key regulators of biological pathways and explore biological function through network analysis, integration and co-visualisation of additional data, and ontology/functional enrichment analysis – helping to build a better view of the wider biological context.

Metabolic network engineering using a systems model based approach
You will work with a model example of metabolic pathways set, coming from the BioModels database, and you will learn how to carry out computational analyses to find common patterns (i.e. set of reactions) in the network. These might include computing feasible pathways through the network, and minimal set of reactions to knock out specific metabolic functions. Visualisation of results will be achieved with an interactive graphical tool available as a web service.

Modelling cell signalling pathways
Curating models of biological processes is an effective training in computational systems biology, where the curators gain an integrative knowledge on biological systems, modelling and bioinformatics. You will learn to encode models of signalling pathways from a recent publication using COPASI and reproduce the simulation results. Furthermore you will learn to annotate models and learn to re-use pre-existing models from open repositories such as BioModels.

Proteomics (data analysis and functional annotation)
In this project, you will obtain real-life proteomics data from clinical tumour samples. Your task will be to process the raw data, analyse the results, and eventually interpret them in a wider context using the Open Targets Platform.

An introduction to deep learning through functional annotation of proteins
Automatically annotating protein sequences with functional information is vital in a world where sequences are produced so fast that humans can’t keep up. In this project you will explore how deep learning can be used to enrich sequences automatically.

Single cell characterization of cell types and cell development
This project will make use of single cell RNA Sequencing data (scRNA-Seq) to show how to: 1) quality control the sequencing data; 2) understand the variances of the data; 3) cluster the cell types; 4) understand the cell development; 5) find differential expression genes that determine the cell types or cell development. You will use data from the Human Cell Atlas and Tabula Muris to understand human and mouse cell types respectively.

Finding and extracting meaningful structural data from PDBe
This project will introduce you to the wealth of data available at PDBe and how this can be extracted to analyse macromolecular structures. You will firstly explore the search and entry pages at PDBe to identify the type of data available for analysis. Using this knowledge, you will then use and adapt template scripts in order to access this data programmatically and analyse a subset of your results. This project should give you the foundation of knowledge about how to access data through the PDBe API, and how you can analyse subsets of PDB data related to your field of expertise.

Exploring variation data across human populations
Natural variation is required to generate the broad range of traits and phenotypes that exist between single individuals and between different populations. In this project you will explore the results of SNP-calling using web-based resources such as Ensembl Variant Effect Predictor. You will predict the functional consequences of variants between separate human populations and identify the variant(s) within your samples that have been associated with several interesting phenotypes.

Instructors and speakers

Scientific Programme Committee

Alexandra Holinski

Sarah Morgan

Cedric Notredame
Centre for Genomic Regulation, Spain

Keynote speakers

Cedric Notredame
Centre for Genomic Regulation, Spain

Virginie Uhlmann

Instructors / Speakers

Alex Bateman EMBL-EBI, UK
Melissa Burke, EMBL-EBI, UK
Paolo Di Tommaso, Centre for Genomic Regulation, Spain
Evan Floden, Centre for Genomic Regulation, Spain
Nikiforos Karamanis, EMBL-EBI, UK
Lee Larcombe, nexaSTEM, UK
Fabio Madeira, EMBL-EBI, UK
Peter McQuilton, University of Oxford, UK
Sarah Morgan, EMBL-EBI, UK
Rabie Saidi, EMBL-EBI, UK

How to apply

This course is aimed at individuals working across biological sciences who have little or no experience in bioinformatics. Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their skills and knowledge further. No previous knowledge of programming / coding is required for this course.

How to Apply
Please complete the online application form. Places are limited and will be awarded on merit. If you have any problems with the online application process, please contact us.

Please note: Applications must be supported by a recommendation from a scientific or clinical sponsor (e.g. supervisor, line manager or head of department). A request for a supporting statement will be sent to your nominated sponsor automatically during the application process. Applicants must ensure that their sponsor provides this supporting statement by the application deadline. Applications without a supporting statement cannot be considered.

Travel visas
Successful applicants will be provided with a support letter for their visa application, if required.

Please visit the following websites for further information on visiting the UK:


Cost Accommodation / meals
Course fee £ 680 This is a residential course and the fee includes all accommodation and meals.

A limited number of registration bursaries are available for PhD students to attend this course (up to 50% of the standard fee).

The following documents will need to be provided:

  • CV
  • Covering letter
  • Letter from supervisor

To apply, please contact the event organiser.

Bursary deadline: 2 April 2019

Additional funding opportunities
Visit our support page for additional financial support currently available.

Extra accommodation
If you wish to book onsite accommodation either side of the course dates, please contact the Conference Centre directly.

Accommodation services phishing scam – please be vigilant. More information.


Feedback from the 2017 course:

”Really great course. I loved the fact that it was very dynamic and everyone participated.”

”This is definitely the best short course I have ever attended. From the application to the follow-up arrangements it has been such a pleasure and a privilege.”

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