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- European Bioinformatics Institute (EBI)7
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- Workshops and courses7
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- Portugal1
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Target audience
- 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. A working knowledge of the Linux operating system and ability to use the command line or experience of using a programming language (e.g Python) would be a benefit but is not mandatory. An undergraduate knowledge of molecular and cellular biology or some background in mathematics is highly beneficial. 1
- This course is aimed at scientists working with bioimage data across the life sciences. It is suitable for those involved in creating bioimages or taking their first steps in analysis. The content would also be suitable for those wanting to learn more about the BioImage Archive and gain experience with machine learning approaches for image analysis. The programme will be of particular interest to bio-image analysts with questions relating to the use of ‘big data’ and using the wealth of publically available data curated in the BioImageArchive. The course should be accessible to members of the bioimaging community and does not require prior experience with machine learning methods or use of the BioImage Archive is necessary, but applicants are encouraged to explore the resources below before starting their application. Applicants should be comfortable with basic programming tasks and have experience working with Python. Prerequisite reading: Nature: BioImage Archive: A call for public archives for biological image data biorxiv: ZeroCostDL4Mic: an open platform to simplify access and use of Deep-Learning in Microscopy Nucleic Acids Research: The BioStudies database—one stop shop for all data supporting a life sciences study Nature Methods: EMPIAR: a public archive for raw electron microscopy image data Nature: Image Data Resource: a bioimage data integration and publication platform BioModelZoo1
- This course is aimed at scientists working with biomage data across the life sciences. It is suitable for those involved in creating bioimages or taking their first steps in analysis. The content would also be suitable for those wanting to learn more about the BioImage Archive and gain experience with machine learning approaches for image analysis. The programme will be of particular interest to bioimage analysts with questions relating to the use of ‘big data’ and using the wealth of publically available data curated in the BioImage Archive. The course should be accessible to members of the bioimaging community and does not require prior experience with machine learning methods or use of the BioImage Archive. Applicants are encouraged to explore the resources below before starting their application. Applicants should be comfortable with basic programming tasks and have experience working with Python. Prerequisite reading: BioImage Archive: A call for public archives for biological image data ZeroCostDL4Mic: an open platform to simplify access and use of Deep-Learning in Microscopy The BioStudies database - one stop shop for all data supporting a life sciences study EMPIAR: a public archive for raw electron microscopy image data Image Data Resource: a bioimage data integration and publication platform BioImage Model Zoo 1
- This course is intended for PhD students of Portuguese and international institutions (with a particular focus on students of the CIBIO-InBIO’s BIODIV, SUSFOR Doctoral Programs and University of Porto), but more experienced researchers that are initiating projects in the field of environmental metagenomics can also participate. Prerequisite knowledge No previous bioinformatics experience is required, but an undergraduate level understanding of biology would be an advantage.1
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Instructor
- Ugis Sarkans
- Aleena Mushtaq29
- Benjamin Moore18
- David Armstrong17
- Michal Szpak17
- Nancy George17
- Birgit Meldal15
- Sarah Morgan14
- Tom Hancocks14
- Alexandra Holinski13
- Baron Koylass13
- Emily Perry13
- Anna Swan12
- Dayane Rodrigues Araujo12
- Sam Holt12
- Kalpana Panneerselvam11
- Lee Larcombe11
- Alex Bateman10
- Alexandre Bonvin10
- Krishna Kumar Tiwari10
- Lorna Richardson10
- Rossana Zaru10
- Wendi Bacon10
- Louisse Paola Mirabueno9
- Osman Salih9
- Rahuman Sheriff9
- Silvie Fexova9
- Thawfeek Mohamed Varusai9
- Typhaine Paysan-Lafosse9
- Ajay Mishra8
- Alexey Larionov8
- Andrew Hercules8
- Cath Brooksbank8
- Eliot Ragueneau8
- Fabio Madeira8
- Hema Bye-A-Jee8
- Emily Bowler-Barnett7
- Gerard Kleywegt7
- Livia Perfetto7
- Nandana Madhusoodanan7
- Pablo Porras Millan7
- Piraveen Gopalasingam7
- Tobias Rausch7
- Francesco Iorio6
- Nikiforos Karamanis6
- Patricia Carvajal Lopez6
- Pedro Raposo6
- Sandra Orchard6
- Astrid Gall5
- Attilio Vittorio Vargiu5
- Blake Sweeney5
- Giuliano Malloci5
- James Stephenson5
- Jonathan Manning5
- Julia Foreman5
- Maira Ihsan5
- Pablo Moreno5
- Paul Denny5
- Piv Gopalasingam5
- Sarah Butcher5
- Thawfeek Varusai5
- Alessandra Villa4
- Anton Petrov4
- Aurelien Dugourd4
- Chris Quince4
- Denise Carvalho-Silva4
- Dona Shaju4
- Erin Haskell4
- Evangelia Petsalaki4
- George Georghiou4
- Girolamo Giudice4
- Gun Antonia Nilsson Lock4
- Henning Hermjakob4
- Irene Papatheodorou4
- Johannes Griss4
- Josephine Burgin4
- Juan Antonio Vizcaino4
- Kalpana Paneerselvam4
- Kostas Billis4
- Leanne Haggerty4
- Lennart Martens4
- Liis Kolberg4
- Marton Olbei4
- Mathieu Bourgey4
- Michele Magrane4
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- Ricard Argelaguet4
- Sara Rocio Chuguransky4
- Simon Andrews4
- Summer Rosonovski4
- Varsha Kale4
- Vera Matser4
- Vytautas Gapsys4
- Yasset Perez-Riverol4
- Yvonne Lussi4
- Zhichao Miao4
- Adam Hospital3
- Adrian Turjanski3
- Alex Mitchell3
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