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Content provider
- European Bioinformatics Institute (EBI)2
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Scientific topic
- Omics
- Cancer4
- Cancer biology4
- Exomes4
- Genome annotation4
- Genomes4
- Genomics4
- Neoplasm4
- Neoplasms4
- Oncology4
- Personal genomics4
- Synthetic genomics4
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- 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
- 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
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- Exome variant detection1
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- Genome variant detection1
- Germ line variant calling1
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- Protein SNP mapping1
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- SNP calling1
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- 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 courses2
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Target audience
- 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
- Sandra Orchard4
- Johannes Griss3
- Lee Larcombe3
- Rachel Lyne3
- Asier Gonzalez2
- Denise Carvalho-Silva2
- Dezso Modos2
- Manik Garg2
- Marton Olbei2
- Pablo Porras Millan2
- Ricard Argelaguet2
- Tamas Korcsmáros2
- Tamás Korcsmáros2
- Yasset Perez Riverol2
- Alejandro Brenes Murillo1
- Alex Bateman1
- Andrew Hercules1
- Andrew Jarnuczak1
- Aurelien Dugourd1
- Britta Velten1
- Claire O’Donovan1
- Danila Bredhkin1
- Danish Memon1
- David Fazekas1
- Elena Lukyanova1
- Francesca Ciccarelli1
- Francesco Iorio1
- Gaurhari Dass1
- Girolamo Giudice1
- Gosia Trynka1
- Hanna Najgebauer1
- Helena Cornu1
- Jacques Serizay1
- Konstantinos Tsirigos1
- Livia Perfetto1
- Magnus Øverlie Arntzen1
- Maria Zimmermann1
- Masa Roller1
- Matthew Hall1
- Melissa Burke1
- Michaela Spitzer1
- Mohamed Alibi1
- Nils Eling1
- Samuel Collombet1
- Sarah Morgan1
- Sergio Contrino1
- Shila Ghazanfar1
- Swee Hoe Ong1
- Tatsuya Nobori1
- Vy Nguyen1
- Yasset Perez-Riverol1
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