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VERSION:2.0
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DTSTAMP:20260716T015011Z
UID:ef3f0528-5c9b-4ba5-8fea-a756e6d653bf
DTSTART:20201012T090000Z
DTEND:20201016T170000Z
DESCRIPTION:This course provides an introduction to the use of bioinformati
 cs in biological research\, giving participants guidance for using bioinfo
 rmatics in their work whilst also providing hands-on training in tools and
  resources appropriate to their research.\n\nParticipants will initially b
 e introduced to bioinformatics theory and practice\, including best practi
 ces for undertaking bioinformatics analysis\, data management and reproduc
 ibility. To enable specific exploration of resources in their particular f
 ield of interest\, participants will be divided into focused groups to wor
 k on a small project set by EMBL-EBI resource and research staff\, ending 
 in a presentation from each group on the final day of the course to bring 
 together learnings from all participants.\n\nThe course includes training 
 and mentoring by experts from EMBL-EBI and external institutes.\n\n**Group
  projects**\n\nA major element of this course is a group project\, where p
 articipants will be placed in small groups to work together on a challenge
  set by trainers from EMBL-EBI. This allows people to explore the bioinfor
 matics tools and resources available in their area of interest and apply t
 hem to a set problem\, providing participants with hands-on experience rel
 evant to their own research. The group work will culminate in a presentati
 on session involving all participants on the final day of the course\, giv
 ing an opportunity for wider discussion on the benefits and challenges of 
 working with biological data.\n\nGroups are mentored and supported by the 
 trainers who set the initial challenge\, but the groups will be responsibl
 e for driving their projects forward\, with all members expected to take a
 n active role. Groups are pre-organised before the course\, and all group 
 members will be sent some short “homework” in preparation for their pr
 oject work prior to the start of the course.\n\nBasic outlines of the proj
 ects on offer this year are given below. In your application you must indi
 cate your first and second choice of project\, based on which you think wo
 uld benefit your research most. Not all projects may be offered\, and fina
 l decisions on which projects will be run during the course will be made b
 ased on the number of applicants per project.\n\nThis year’s projects ar
 e as follows:\n\n**Networks and pathways**\n\nThis project will make use o
 f gene expression data (RNA-seq) to build protein-protein interaction netw
 orks\, which can be used to explore functional relationships between the (
 potentially) expressed protein products. You will use Cytoscape to visuali
 se protein networks\, identify key regulators of biological pathways and e
 xplore biological function through network analysis\, integration and co-v
 isualisation of additional data\, and ontology/functional enrichment analy
 sis - helping to build a better view of the wider biological context.\n\n*
 *Modelling cell signalling pathways**\n\nCurating models of biological pro
 cesses is an effective training in computational systems biology\, where t
 he curators gain an integrative knowledge of biological systems\, modellin
 g and bioinformatics. You will learn to encode computational models of sig
 nalling pathways from a recent publication using COPASI and how to reprodu
 ce the simulation results. Furthermore\, you will learn how to annotate mo
 dels and re-use pre-existing models from open repositories such as BioMode
 ls.\n\n**Genome variation across human populations**\n\nNatural variation 
 between individuals or between different human populations is a result of 
 genome mutations throughout evolutionary history. Some mutations may becom
 e fixed because of their beneficial effect while most drift among individu
 als. During this project\, you will investigate genomic variation between 
 two separate human populations of European and Asian descent. Using sequen
 ce data from a number of individuals from each population\, you will use a
  range of bioinformatics tools to discover variants that exist between the
 m. In the second section of the project\, you will attempt to analyse the 
 functional consequences of the variants you have identified\, linking them
  to phenotypes.\n\n**Metabolic network engineering using a systems model-b
 ased approach**\n\nMetabolic pathway analysis helps to identify the struct
 ure and dynamics of a metabolic network and thereby also allow us to have 
 an insight into cell physiology which is the foundation of metabolic engin
 eering. You will work with a curated model related to a metabolism network
  chosen from BioModels\, and learn how to carry out computational analyses
  to find common patterns in the networks. These might include computing fe
 asible pathways through the network and minimal reactions to knock out spe
 cific metabolic functions\, along with visualisation and exploration to ga
 in a further insight into the results.\n\n**Finding and interpreting publi
 cly available structural data **\n\nThis project will introduce you to th
 e wealth of publicly available structural data and give you the opportunit
 y to investigate how this data can be used to analyse macromolecular struc
 tures. You will firstly explore the search and entry pages at PDBe to iden
 tify the type of data available for analysis. Then using this knowledge\, 
 you will discover how to access this data programmatically and analyse a s
 ubset of your results to interpret biological relevance. \n\n**Functional
  annotation of proteins**\n\nFunctional annotation refers to discovering t
 he functions of proteins. Participants will  annotate a protein of intere
 st which has not been annotated previously\, either manually or by any Uni
 Prot automatic system. Participants will use different ways to discover th
 e function of their protein of interest from alignment to machine learning
 . You will learn the different annotation types in UniProtKB and how to us
 e the UniProt resources for their investigation. You will also learn how t
 o build machine learning models\, from dataset construction to prediction.
SUMMARY:Summer school in bioinformatics (Virtual)
URL;VALUE=URI:https://www.ebi.ac.uk/training/events/summer-school-bioinform
 atics-virtual
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