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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
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- Whole genomes4
- Chromosome walking2
- Clone verification2
- DNA-Seq2
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- High throughput sequencing2
- High-throughput sequencing2
- NGS2
- NGS data analysis2
- Next gen sequencing2
- Next generation sequencing2
- Omics2
- Panels2
- Primer walking2
- Sanger sequencing2
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- Targeted next-generation sequencing panels2
- Allele calling1
- CNV deletion1
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- Copy number variant1
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- Data analysis1
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- Exome variant detection1
- Genetic variation analysis1
- Genetic variation annotation1
- Genome variant detection1
- Germ line variant calling1
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- Network1
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- 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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- 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
- Janick Mathys143
- Bruna Piereck72
- Alexander Botzki67
- Wandrille Duchemin57
- True Colours48
- Christof De Bo45
- Matheus Lourenço42
- Benjamin Pavie38
- Elien Vandermarliere34
- Lieve Ongena34
- Geert van Geest33
- Aleena Mushtaq29
- Robin Engler29
- René Custers23
- Amanda Gonçalves19
- Benjamin Moore18
- Gert Van Isterdael18
- Joris De Wolf18
- Niels Vandamme18
- Agnes Uhereczky17
- David Armstrong17
- Liesbeth De Milde17
- Michal Szpak17
- Nancy George17
- Robin Lefebvre17
- Deepak Tanwar16
- Lucia Smit16
- Birgit Meldal15
- James Collier14
- Kobe Lavaerts14
- Sarah Morgan14
- Tom Hancocks14
- Wendi Bacon14
- Alexandra Holinski13
- 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
- Barbara Baert10
- 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
- Osman Salih9
- Rahuman Sheriff9
- Silvie Fexova9
- Tallulah Andrews9
- Thawfeek Mohamed Varusai9
- Thuong Van Du Tran9
- Typhaine Paysan-Lafosse9
- Alexey Larionov8
- Andrew Hercules8
- Bart Mesuere8
- Ben Verhoeven8
- Cath Brooksbank8
- Eliot Ragueneau8
- 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
- Evelien Van Hamme7
- Gerard Kleywegt7
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