- Home
- Events
Filters
Sort
-
-
Filter Clear filters
-
-
Start
- -
-
-
-
Content provider
- European Bioinformatics Institute (EBI)25
- Show N_FILTERS more
-
-
-
Keyword
- DNA & RNA (dna-rna)
- HDRUK1019
- bioinformatics57
- NGS36
- R33
- RNA-seq26
- Ensembl24
- data analysis17
- Ensembl Variant Effect Predictor16
- Ensembl Genomes14
- online14
- data science13
- Open Targets12
- R-programming11
- Proteins (proteins)9
- DNA-seq8
- galaxy8
- variant-calling8
- Bioinformatics7
- statistics7
- Project management6
- Expression Atlas5
- IntAct Molecular Interaction Database5
- Reactome pathways database5
- Structures (structures)5
- Team building5
- UniProt: The Universal Protein Resource5
- transcriptomics5
- Budgeting4
- CNV analysis4
- CRISPR-Cas94
- Core facility services4
- Data integration4
- Data management4
- Galaxy for metabolomics4
- InterPro4
- Long-read RNA-seq4
- MS Imaging4
- Metabolite identification4
- Principal investigators4
- Protein Data Bank in Europe4
- Protein Data Bank in Europe - Knowledge Base4
- SNV analysis4
- bash4
- dplyr4
- ggplot24
- microscopy4
- unix4
- BioImage Archive3
- BioModels database3
- Bioimage analysis3
- Cross domain (cross-domain)3
- Deep learning3
- European Genome-phenome Archive3
- European Nucleotide Archive3
- European Variation Archive3
- Logic modelling3
- Multi-Omics Factor Analysis3
- NHGRI-EBI GWAS Catalog3
- Network inference3
- Python3
- biostatistics3
- data visualization3
- functional genomics3
- lipidomics3
- protein function3
- single-cell3
- toxicogenomics3
- Statistics2
- 10X2
- ATAC-seq2
- AlphaFold Database2
- ChIP-Seq2
- Complex Portal2
- Cytoscape2
- Data analysis2
- Data carpentry2
- Data exploration2
- Diagnosis2
- Electron Microscopy Data Bank2
- Electron Microscopy Public Image Archive - EMPIAR2
- Europe PMC2
- Galaxy2
- Gene expression (gene-expression)2
- Genome variation2
- Genomics2
- HMMER - protein homology search2
- HPC2
- Human ecosystems2
- ISCB2
- Introduction2
- Long reads2
- MOFA2
- MetaboLights: Metabolomics repository and reference database2
- Metabolights2
- Metabolomics2
- Modelling cell signalling2
- MolecularCellBiology2
- Next-generation sequencing2
- OtherEvents2
- Show N_FILTERS more
-
-
-
Scientific topic
- Bioinformatics16
- Chromosome walking5
- Clone verification5
- DNA-Seq5
- DNase-Seq5
- Exomes5
- Genome annotation5
- Genomes5
- Genomics5
- High throughput sequencing5
- High-throughput sequencing5
- NGS5
- NGS data analysis5
- Next gen sequencing5
- Next generation sequencing5
- Panels5
- Personal genomics5
- Primer walking5
- Sanger sequencing5
- Sequencing5
- Synthetic genomics5
- Targeted next-generation sequencing panels5
- Viral genomics5
- Whole genomes5
- Allele calling3
- Exome variant detection3
- Genome variant detection3
- Germ line variant calling3
- Mutation detection3
- Somatic variant calling3
- Variant calling3
- Variant mapping3
- de novo mutation detection3
- Cancer2
- Cancer biology2
- Neoplasm2
- Neoplasms2
- Oligonucleotide alignment2
- Oligonucleotide alignment construction2
- Oligonucleotide alignment generation2
- Oligonucleotide mapping2
- Oncology2
- Read alignment2
- Read mapping2
- Short oligonucleotide alignment2
- Short read alignment2
- Short read mapping2
- Short sequence read mapping2
- Accession mapping1
- Biological models1
- Biological networks1
- Biological pathways1
- Biomolecular simulation1
- CNV deletion1
- CNV duplication1
- CNV insertion / amplification1
- Cellular process pathways1
- Codon usage1
- Complex CNV1
- Copy number variant1
- Copy number variation1
- DNA chips1
- DNA microarrays1
- Data visualisation1
- Disease pathways1
- Environmental information processing pathways1
- Expression1
- Functional genomics1
- Fusion genes1
- Gene expression1
- Gene expression profiling1
- Gene features1
- Gene regulatory networks1
- Gene structure1
- Gene transcription1
- Gene translation1
- Genetic information processing pathways1
- ID mapping1
- Identifier mapping1
- Interactions1
- Interactome1
- Metabolic pathways1
- MicroRNA sequencing1
- Molecular interactions1
- Molecular interactions, pathways and networks1
- Molecular visualisation1
- Network1
- Networks1
- Omics1
- Pathway1
- Pathway or network1
- Pathways1
- Plotting1
- RNA sequencing1
- RNA-Seq1
- RNA-Seq analysis1
- Rendering1
- SNP calling1
- SNP detection1
- SNP discovery1
- Show N_FILTERS more
-
-
-
Event type
- Workshops and courses25
- Show N_FILTERS more
-
-
-
Country
- United Kingdom
- Brazil1
- Show N_FILTERS more
-
-
-
Target audience
- Bioinformaticians and wet-lab biologists who can program in Python or R.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 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 life science researchers needing to learn more about the basic processing of raw RNA-Seq data and downstream analysis. It will help those wanting to learn how to interpret gene expression data and explore results of biological significance from processed data. 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 researchers who are generating, planning on generating, or working with single cell RNA sequencing or image-based transcriptomics data. This course will not cover any aspects of data analysis, therefore no prior computational knowledge is required.1
- Wet-lab researchers and bioinformaticians1
- Show N_FILTERS more
-
- Only show online events
- Hide past events
- Show disabled events