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Keyword
- HDRUK15
- DNA & RNA (dna-rna)5
- CNV analysis3
- CRISPR-Cas93
- Ensembl3
- Long-read RNA-seq3
- SNV analysis3
- European Nucleotide Archive2
- European Variation Archive2
- Long reads2
- NGS2
- analysis pipeline2
- genome graph2
- next-generation sequencing2
- read mapping2
- sequence alignment and mapping (SAM)2
- Biotherapeutics1
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Scientific topic
- Genomics
- Bioinformatics452
- Data visualisation154
- Data rendering150
- Data mining110
- Pattern recognition110
- Aerobiology87
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- Functional genomics58
- Comparative transcriptomics56
- Transcriptome56
- Transcriptomics56
- Genome annotation44
- Exomes43
- Genomes43
- Personal genomics43
- Synthetic genomics43
- Viral genomics43
- Whole genomes43
- Active learning28
- Ensembl learning28
- Kernel methods28
- Knowledge representation28
- Machine learning28
- Neural networks28
- Recommender system28
- Reinforcement learning28
- Supervised learning28
- Unsupervised learning28
- Bottom-up proteomics25
- Discovery proteomics25
- MS-based targeted proteomics25
- MS-based untargeted proteomics25
- Metaproteomics25
- Peptide identification25
- Protein and peptide identification25
- Proteomics25
- Quantitative proteomics25
- Targeted proteomics25
- Top-down proteomics25
- Biological modelling24
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- Systems biology24
- Systems modelling24
- Exometabolomics21
- LC-MS-based metabolomics21
- MS-based metabolomics21
- MS-based targeted metabolomics21
- MS-based untargeted metabolomics21
- Mass spectrometry-based metabolomics21
- Metabolites21
- Metabolome21
- Metabolomics21
- Metabonomics21
- NMR-based metabolomics21
- Python20
- Python program20
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- py20
- Biomedical research16
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- Fusion genes16
- Gene features16
- Gene structure16
- General medicine16
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- Medicine16
- Bioimaging15
- Biological imaging15
- Coding RNA15
- EST15
- Exons15
- Fusion transcripts15
- Gene transcript features15
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- Introns15
- PolyA signal15
- PolyA site15
- Signal peptide coding sequence15
- Transit peptide coding sequence15
- cDNA15
- mRNA15
- mRNA features15
- Phylogenetics14
- ChIP-exo12
- ChIP-seq12
- ChIP-sequencing12
- Chip Seq12
- Chip sequencing12
- Chip-sequencing12
- RNA-Seq analysis12
- Chromosome walking11
- Clone verification11
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Venue
- European Bioinformatics Institute, Hinxton9
- Craik-Marshall Building7
- European Bioinformatics Institute4
- Online, West Mains Road3
- Birmingham Metabolomics Training Centre1
- Dexter House1
- EMBL1
- EMBL-EBI1
- Kings Buildings, The University of Edinburgh, Easter Bush campus1
- Kings Buildings, The University of Edinburgh, Murchison House G07, Kings Buildings campus1
- Online1
- The King's Buildings, The University of Edinburgh1
- The King's Buildings, The University of Edinburgh, West Mains Road1
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Country
- United Kingdom
- United States of America57
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Target audience
- Graduate students7
- Institutions and other external Institutions or individuals7
- Postdocs and Staff members from the University of Cambridge7
- The course is aimed primarily at mid-career scientists – especially those whose formal education likely included statistics2
- but who have not perhaps put this into practice since.2
- The handson component is aimed at novice to intermediate users who are seeking detailed guidance with GATK and related tools.1
- The lecture based component of the workshop is aimed at a mixed audience of people who are new to the topic of variant discovery or to GATK1
- 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 aimed at PhD students and post-doctoral researchers who are using high-throughput sequencing technologies and bioinformatics methods in their research. The content is most applicable for those working with eukaryotic genomes, human genetics and in rare disease research. Participants will require a basic knowledge of the Unix command line, the Ubuntu 16 operating system and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials: www.r-tutor.com/r-introduction Please note: participants without basic knowledge of these resources will have difficulty in completing the practical sessions.1
- This course is aimed at PhD students and postdoctoral researchers needing to learn about methods and approaches for manipulating and analysing livestock genomic data. It will help those wanting to start basic identification of genetic variation, annotating function to genomic data, and using public data to interpret new findings. Participants will require a basic knowledge of the Unix command line, the Ubuntu 18 operating system and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials: www.r-tutor.com/r-introduction Regardless of your current knowledge we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area. 1
- 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.1
- This course is suitable for all users who have an interest in Clinical Genetics with a special emphasis on rare disorders. It is also pertinent to those who seek to develop a better understanding of the role of accurate phenotyping in aiding the interpretation of filtered variants in patients and understanding genotype-phenotype correlations.1
- Wet-lab researchers and bioinformaticians1
- or who are already GATK users seeking to improve their understanding of and proficiency with the tools.1
- seeking an introductory course into the tools1
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Eligibility
- First come first served2
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