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DTSTAMP:20260831T210010Z
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DTSTART:20220613T090000Z
DTEND:20220617T170000Z
DESCRIPTION:This course\, organised in association with Wellcome Connecting
  Science\, provides an introduction to the use of bioinformatics in biolog
 ical research\, giving participants guidance for using bioinformatics in t
 heir work whilst also providing hands-on training in tools and resources a
 ppropriate to their research.\n\nParticipants will initially be introduced
  to bioinformatics theory and practice\, including best practices for unde
 rtaking bioinformatics analysis\, data management\, and reproducibility. T
 o enable specific exploration of resources in their particular field of in
 terest\, participants will be divided into focused groups to work on a pro
 ject set by resource and data experts from EMBL-EBI and external collabora
 ting institutes. These projects will end with a presentation from each gro
 up on the final day of the course to bring together learnings from all par
 ticipants.\n\nParticipants will be required to review some pre-recorded ma
 terial prior to the start of the course and will have an opportunity to me
 et other trainees in an induction session to be held virtually in the week
  before the course take place.\n\n### Group projects\n\nA major element of
  this course is a group project\, where participants will be placed in sma
 ll groups to work together on a challenge set by trainers from EMBL-EBI an
 d external institutes. This allows people to explore the bioinformatics to
 ols and resources available in their area of interest and apply them to a 
 set problem\, providing participants with hands-on experience relevant to 
 their own research. The group work will culminate in a presentation sessio
 n involving all participants on the final day of the course\, giving an op
 portunity for wider discussion on the benefits and challenges of working w
 ith biological data.\n\nGroups are mentored and supported by the trainers 
 who set the initial challenge\, but the groups will be responsible for dri
 ving their projects forward\, with all members expected to take an active 
 role. Groups are pre-organised before the course\, and all group members w
 ill be sent some short “homework” in preparation for their project wor
 k prior to the start of the course.\n\nBasic outlines of the projects on o
 ffer this year are given below. In your application you must indicate your
  first and second choice of project\, based on which you think would benef
 it your research most. Not all projects may be offered\, and final decisio
 ns on which projects will be run during the course will be made based on t
 he number of applicants per project.\n\nMost of the projects cover mammali
 an data sets\, however\, in many cases\, the methods and approaches taught
  are transferable to data from various species.\n\n**Networks and pathways
 **\n\nThis project will cover typical bioinformatics analysis steps needed
  to put differentially expressed genes into a wider biological context. Yo
 u will start with gene expression data (RNA-seq) to build an initial inter
 action network. Next\, you will learn to combine public network datasets\,
  identify key regulators of biological pathways\, and explore biological f
 unction through network analysis. You will get first-hand experience in in
 tegration and co-visualising with additional data and functional enrichmen
 t analysis. All this helps to put the initial results into a previously kn
 own context and provide hypotheses for potential follow up experiments. We
  will use [Cytoscape](https://cytoscape.org/)\, [Expression Atlas](https:/
 /www.ebi.ac.uk/gxa/home)\, [g:Profiler](https://biit.cs.ut.ee/gprofiler/go
 st)\, [StringDb](https://string-db.org/)\, among other tools. We also may 
 give a few R packages a try.\n\nProject mentors: Priit Adler (University 
 of Tartu)\, Hedi Peterson (University of Tartu)\n\n**Genome variation acr
 oss human populations**\n\nNatural variation between individuals or betwee
 n different human populations is a result of genome mutations throughout e
 volutionary history. Some mutations may become fixed because of their bene
 ficial effect while most drift among individuals. During this project\, yo
 u will investigate genomic variation between two separate human population
 s of European and Asian descent. Using sequence data from a number of indi
 viduals from each population\, you will use a range of bioinformatics tool
 s to discover variants that exist between them. In the second section of t
 he project\, you will attempt to analyse the functional consequences of th
 e variants you have identified\, linking them to phenotypes.\n\nProject me
 ntors: Baron Koylass (EMBL-EBI)\n\n**Modelling cell signalling pathways**
 \n\nCurating models of biological processes is an effective training in co
 mputational systems biology\, where the curators gain an integrative knowl
 edge of biological systems\, modelling\, and bioinformatics. You will lear
 n to encode and simulate ordinary differential equation models of signalli
 ng pathways from a recent publication using user-friendly software such as
  [COPASI](http://copasi.org/) even without extensive mathematical backgrou
 nd. You will learn to perform in-silico experiments\, new predictions\, an
 d develop hypotheses. Furthermore\, you will learn how to annotate models 
 and re-use pre-existing models from open repositories such as [BioModels](
 https://www.ebi.ac.uk/biomodels/).\n\nProject mentors: Rahuman Sheriff (E
 MBL-EBI) \n\n**Interpreting functional information from large scale prote
 in structure data**\n\nThis project will introduce you to the wealth of pu
 blicly available data in the [Protein Data Bank](https://www.ebi.ac.uk/pdb
 e/) (PDB) and give you the opportunity to investigate how large subsets of
  structure data can be used to analyse protein features and determine func
 tion. In the project you will learn how to: identify relevant protein stru
 ctures\, collate and interpret functional information\, and implement this
  process programmatically.\n\nProject mentors: David Armstrong (EMBL-EBI)
 \, Preeti Choudhary (EMBL-EBI)\n\n**Analysis of intercellular interaction
 s in healthy and diseased states**\n\nUlcerative colitis is an inflammator
 y bowel disease. The exact pathomechanism of the disease is unknown. Howev
 er\, the interactions between the intestinal immune cells and the intestin
 al epithelial cells play a crucial role during the development of the dise
 ase. Single-cell RNA-seq measurements can help us understand these complex
  interactions. The expression data combined with protein-protein interacti
 on databases can shed light on the connections between cells in diseased a
 nd healthy states.\n\nDuring this project\, you will use a single-cell RNA
 -seq dataset to build interactions between the various cells. The dataset 
 contains pre-processed\, cell type classified data of biopsies from health
 y\, inflamed and non-inflamed UC colonic biopsies. The interactions betwee
 n cells will be downloaded from the [OmniPath](https://omnipathdb.org/) da
 tabase. You will use Python Notebooks to build up the intercellular networ
 ks\, map the single cell RNA-seq expression data and visualise them. The i
 ntercellular networks between various cell types can then be compared by [
 Cytoscape](https://cytoscape.org/).\n\nProject mentors: Dezso Modos (Quad
 ram Institute)\, Marton Olbei (Earlham Institute)
LOCATION:European Bioinformatics Institute\, Hinxton
SUMMARY:Summer school in bioinformatics
URL;VALUE=URI:https://www.ebi.ac.uk/training/events/summer-school-bioinform
 atics-2022
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