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- 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
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- 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
- Janick Mathys143
- Bruna Piereck72
- Alexander Botzki68
- Wandrille Duchemin57
- Matheus Lourenço48
- True Colours48
- Christof De Bo45
- Benjamin Pavie38
- Elien Vandermarliere34
- Lieve Ongena34
- Geert van Geest33
- Aleena Mushtaq29
- Robin Engler29
- René Custers23
- Agnes Uhereczky21
- Gert Van Isterdael20
- Lucia Smit20
- Amanda Gonçalves19
- Benjamin Moore18
- Joris De Wolf18
- Niels Vandamme18
- David Armstrong17
- Liesbeth De Milde17
- Michal Szpak17
- Nancy George17
- Robin Lefebvre17
- Deepak Tanwar16
- Birgit Meldal15
- James Collier14
- Kobe Lavaerts14
- Sarah Morgan14
- Tom Hancocks14
- Wendi Bacon14
- Alexandra Holinski13
- Barbara Baert13
- Baron Koylass13
- Emily Perry13
- Sebastian Munck13
- Anna Swan12
- Dayane Rodrigues Araujo12
- Sam Holt12
- Tania Wyss Lozano12
- Tatiana Woller12
- David Wishart11
- Kalpana Panneerselvam11
- Lee Larcombe11
- Nicolas Vannieuwkerke11
- Ricard Argelaguet11
- Alex Bateman10
- Alexandre Bonvin10
- Gustavo Ruiz Buendia10
- Krishna Kumar Tiwari10
- Lorna Richardson10
- Malachi Griffith10
- Niels Geudens10
- Rossana Zaru10
- Veronique Voisin10
- An Staes9
- Bob Asselbergh9
- Frédéric Burdet9
- Gary Bader9
- Jolan Heyse9
- Lennart Martens9
- Lieven Clement9
- Louisse Paola Mirabueno9
- Mathieu Bourgey9
- Obi Griffith9
- Rahuman Sheriff9
- Silvie Fexova9
- Tallulah Andrews9
- Thawfeek Mohamed Varusai9
- Thuong Van Du Tran9
- Typhaine Paysan-Lafosse9
- Ajay Mishra8
- Alexey Larionov8
- Andrew Hercules8
- Bart Mesuere8
- Ben Verhoeven8
- Cath Brooksbank8
- Eliot Ragueneau8
- Evelien Van Hamme8
- Fabio Madeira8
- Frank Vernaillen8
- Geert Vermaerke8
- Hema Bye-A-Jee8
- Jared Simpson8
- Jean-luc Doumont8
- Koen Van den Eeckhout8
- Nicolas Peredo8
- Pavankumar Videm8
- Rachel Marcone8
- Tania Wyss8
- Trevor Pugh8
- Alyona Ivanova7
- Arne Defauw7
- Bart Ghesquière7
- Emily Bowler-Barnett7
- Engy Nasr7
- Gerard Kleywegt7
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