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Content provider
- European Bioinformatics Institute (EBI)8
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Scientific topic
- Cancer4
- Cancer biology4
- Exomes4
- Genome annotation4
- Genomes4
- Genomics4
- Neoplasm4
- Neoplasms4
- Oncology4
- Personal genomics4
- Synthetic genomics4
- Viral genomics4
- Whole genomes4
- Chromosome walking2
- Clone verification2
- DNA-Seq2
- DNase-Seq2
- High throughput sequencing2
- High-throughput sequencing2
- NGS2
- NGS data analysis2
- Next gen sequencing2
- Next generation sequencing2
- Omics2
- Panels2
- Primer walking2
- Sanger sequencing2
- Sequencing2
- Targeted next-generation sequencing panels2
- Allele calling1
- CNV deletion1
- CNV duplication1
- CNV insertion / amplification1
- Complex CNV1
- Copy number variant1
- Copy number variation1
- Data analysis1
- Data architecture1
- Data architecture, analysis and design1
- Data design1
- Data rendering1
- Data visualisation1
- Exome variant detection1
- Genetic variation analysis1
- Genetic variation annotation1
- Genome variant detection1
- Germ line variant calling1
- Mutation detection1
- Network1
- Pathway1
- Pathway or network1
- Protein SNP mapping1
- Protein mutation modelling1
- Protein stability change prediction1
- SNP calling1
- SNP detection1
- SNP discovery1
- Sequence variation analysis1
- Single nucleotide polymorphism detection1
- Somatic variant calling1
- Structural assignment1
- Structural biology1
- Structural determination1
- Structure determination1
- Transcript variant analysis1
- Variant analysis1
- Variant calling1
- Variant effect prediction1
- Variant functional prediction1
- Variant mapping1
- de novo mutation detection1
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Event type
- Workshops and courses8
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Country
- United Kingdom4
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Target audience
- This course is aimed at advanced PhD students and post-doctoral researchers who are applying or planning to apply high throughput sequencing technologies in cancer research and wish to familiarise themselves with bioinformatics tools and data analysis methodologies specific to cancer data. Familiarity with the technology and biological use cases of high throughput sequencing is required, as is some experience with R/Bioconductor (basic understanding of the R syntax and ability to manipulate R objects) and the Unix/Linux operating system.2
- No prior experience of bioinformatics is required, but an interest in finding out more about genetic variation resources and an undergraduate level understanding of biology would be of benefit. Experience with command line usage would be very beneficial. This workshop will focus specifically on human genetic variation. Prerequisite We encourage the audience to go through our online course on human genetic variation prior to attending the workshop - www.ebi.ac.uk/training/online/course/human-genetic-variation-i-introduction-2019 .1
- This course is aimed at PhD students and post-doctoral researchers who are applying or planning to apply high throughput sequencing technologies in cancer research and wish to familiarise themselves with bioinformatics tools and data analysis methodologies specific to cancer data. Familiarity with the technology and biological use cases of high throughput sequencing (HTS) is required, as is some experience with R/Bioconductor (basic understanding of the R syntax and ability to manipulate R objects) and the Unix/Linux operating system.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 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 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-introduction1
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Instructor
- Ajay Mishra
- 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
- 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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