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Content provider
- European Bioinformatics Institute (EBI)9
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Keyword
- Proteins (proteins)5
- Electron Microscopy Public Image Archive - EMPIAR4
- InterPro4
- UniProt: The Universal Protein Resource4
- Complex Portal3
- HMMER - protein homology search3
- IntAct Molecular Interaction Database3
- PDBeFold3
- Pfam3
- Protein classification3
- Reactome pathways database3
- Protein sequence2
- Protein structure2
- Structures (structures)2
- AlphaFold Database1
- BioImage Archive1
- BioStudies Database1
- Bioimage analysis1
- Electron Microscopy Data Bank1
- Electron microscopy1
- InterProScan1
- Light microscopy1
- Machine learning models1
- Protein Data Bank in Europe1
- Protein Data Bank in Europe - Knowledge Base1
- Protein- protein interaction1
- Protein-protein interaction1
- Scientific computing1
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Scientific topic
- Protein bioinformatics3
- Protein databases3
- Protein informatics3
- Proteins3
- Gene and protein families2
- Gene families2
- Gene family2
- Gene system2
- Genes, gene family or system2
- Protein families2
- Protein sequence classification2
- Protein structure2
- Protein structures2
- Structural assignment2
- Structural biology2
- Structural determination2
- Structure determination2
- Active learning1
- Amino acid sequence1
- Amino acid sequences1
- Bioimaging1
- Biological imaging1
- Biological pathway analysis1
- Biological pathway modelling1
- Biological pathway prediction1
- Biomolecular structure1
- Computational structural biology1
- Electron density map1
- Ensembl learning1
- Functional pathway analysis1
- Image analysis1
- Kernel methods1
- Knowledge representation1
- Machine learning1
- Molecular structure1
- Neural networks1
- Pathway analysis1
- Pathway comparison1
- Pathway modelling1
- Pathway prediction1
- Pathway simulation1
- Protein complex1
- Protein sequence1
- Protein sequences1
- Recommender system1
- Reinforcement learning1
- Structural bioinformatics1
- Structure analysis1
- Structure data resources1
- Structure databases1
- Structures1
- Supervised learning1
- Unsupervised learning1
- protein1
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Event type
- Workshops and courses9
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Country
- United Kingdom4
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Target audience
- 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 session on programmatic access a 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 at EMBL-EBI please watch our webinar.1
- 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 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 aimed at wet-lab scientists generating structural data or scientists utilising structural data in their analysis and/or interpretation. No previous experience in the field of structural bioinformatics is required, however a basic knowledge of protein structure would be of benefit. Prerequisites A working knowledge of the Linux operating system and ability to use the command line would be a benefit but is not mandatory. 1
- This course is aimed at scientists generating structural data or scientists utilising structural data in their analysis and/or interpretation. No previous experience in the field of structural bioinformatics is required, however a basic knowledge of protein structure would be of benefit.1
- This course is for biological researchers who want to learn more about the application of structural information in their work and how to use some of the key bioinformatics resources that are available. No previous experience in the field of structural bioinformatics is required, however a basic knowledge of protein structure would be of benefit. Participants should be familiar with basic Linux operations - http://www.ee.surrey.ac.uk/Teaching/Unix/ - and have some experience of bioinformatics tools and databases.1
- This workshop is aimed at anyone interested in finding out more about protein biology. No prior experience of bioinformatics is required, but an undergraduate level understanding of biology would be of benefit.1
- This workshop 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. Those who are graduate students, postdocs and staff members from the University of Cambridge, affiliated institutions and other external Institutions or individuals, are invited to apply.1
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Instructor
- Osman Salih
- 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
- 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
- Ugis Sarkans7
- 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
- Peter McQuilton4
- Preeti Choudhary4
- 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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