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- European Bioinformatics Institute (EBI)10
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Target audience
- The course is aimed at research scientists with a minimum of a degree in a biological discipline, including laboratory and clinical staff, as well as specialists in related fields. The practical elements of the course will take raw data from a proteomics experiment and analyse it. Participants will be able to go from MS spectra to identifying and quantify peptides and finally to obtain lists of protein identifiers that can be analysed further using a wide range of resources. The final aim is to provide attendees with the practical bioinformatics knowledge they need to go back to the lab and process their own data when collected.1
- The workshop is aimed at biologists and computer scientists in Latin American countries only (excluding Chile and Uruguay due to funding restrictions) wanting to learn the basics of network analysis and biological data cure for clinically relevant pathogens. Trainees should be undertaking research at postgraduate-level upwards focusing on infectious diseases. No previous experience using interaction data resources is needed. Please note this course will be taught in English, however the trainers are fluent in either Spanish/Portuguese, and can offer language support where feasible. Priority will also be given to those who have not attended the CABANA event yet. Researchers who apply for CABANA courses should have projects in one or more of the CABANA challenge areas (sustainable crop production, communicable diseases, protection of biodiversity). Scientists from underrepresented ethnic and gender groups are especially encouraged to apply for this workshop, for example women and those with Black and/or Indigenous heritage. Prerequisites Participants will require a basic knowledge of the Unix command line, and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials: www.r-tutor.com/r-introduction1
- This course is aimed at anyone interested in finding out more about protein biology. No prior experience of bioinformatics is required, but participants should have an undergraduate level understanding of biology. For those who wish to attend the sessions on programmatic access, prior knowledge of coding/programming would be of benefit. For an introduction to the concept of web services and how you can use them to access the tools and data available programmatically, please watch this EMBL-EBI, programatically webinar.1
- This course is aimed at life science researchers wanting to learn more about processing RNA-seq data and later downstream analysis. It will help those wanting a basic introduction to handling RNA-seq data, guiding them through several common approaches that can be applied to their own datasets. It features taught and practical sessions that cover how to interpret gene expression data and learn more about the biological significance of certain results. Participants will require a basic knowledge of the Unix command line, the Ubuntu 18 operating system, and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials: www.r-tutor.com/r-introduction Regardless of your current knowledge, we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area.1
- This introductory course is aimed at biologists who are embarking on multiomics projects and computational biologists / bioinformaticians who wish to gain a better knowledge of the biological challenges presented when working with integrated datasets. Some practical sessions in the course require a basic understanding of the Unix command line and the R statistics package. If you are not already familiar with these then please ensure that you complete these free tutorials before you attend the course: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Basic R concept tutorials: www.r-tutor.com/r-introduction For advanced-level training in using large-scale multiomics data and machine learning to infer biological models you may wish to consider our course on Systems Biology: From large datasets to biological insight.1
- This workshop is aimed at PhD students within the PhD programme "Genetics, Molecular and Cellular Biology" (University of Pavia) and the PhD programmme "Biomolecular Sciences and Biotechnology" (IUSS, University School for Advanced Studies Pavia. No knowledge of programming is required, but an undergraduate level knowledge of biology or molecular biology would be useful.1
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Instructor
- Kalpana Panneerselvam3
- Thawfeek Varusai3
- Andrew Hercules2
- Birgit Meldal2
- David Armstrong2
- Eliot Ragueneau2
- Johannes Griss2
- Nancy George2
- Nandana Madhusoodanan2
- Rossana Zaru2
- Sara Rocio Chuguransky2
- Typhaine Paysan-Lafosse2
- Yasset Perez-Riverol2
- Adnan Malik1
- Adrian Turjanski1
- Ajay Mishra1
- Alexandra Holinski1
- Andre Fujita1
- Anton Petrov1
- Artur Trancoso Lopo de Queiroz1
- Aurelien Luciani1
- Aurélien Luciani1
- Blake Sweeney1
- Carlos Garcia Giron1
- Chandra Chilamakuri1
- Christoph Wichmann1
- Danish Memon1
- Dario Fernández Do Porto1
- David García Seisdedos1
- Deborah Harrus1
- Deepti Kundu1
- Dezso Modos1
- Emily Perry1
- Ernesto Perez-Rueda1
- Harald Barsnes1
- Helder Nakaya1
- Hema Bye-A-Jee1
- Henning Hermjakob1
- Irene Papatheodorou1
- Jamie Allen1
- Jonathan Manning1
- Juan Antonio Vizcaino1
- Julieth Irene Murillo Silva1
- Kalpana Paneerselvam1
- Kathryn Lilley1
- Keeva Cochrane1
- Kiyoshi Fukutani1
- Kostas Billis1
- Krishna Kumar Tiwari1
- Leanne Haggerty1
- Lee Larcombe1
- Lennart Martens1
- Lieven Clement1
- Liis Kolberg1
- Magnus Øverlie Arntzen1
- Manik Garg1
- Maria Zimmermann1
- Markus Krummenacker 1
- Marton Olbei1
- Oliver Crook1
- Osman Salih1
- Pablo Ivan Pereira Ramos1
- Pablo Porras Millan1
- Paul Denny1
- Pedro Raposo1
- Peli Kyriakidou1
- Peter Karp1
- Piv Gopalasingam1
- Rachel Lyne1
- Samuel Collombet1
- Sandra Orchard1
- Sergio Contrino1
- Simon Andrews1
- Suzanne Paley1
- Tamás Korcsmáros1
- Tom Hancocks1
- Vy Nguyen1
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