- Home
- Events
Filter
Sort
-
-
Filter Clear filters
-
-
Start
- -
-
-
-
Keyword
- Galaxy4
- RNA-Seq4
- RNA-seq4
- Transcriptomics4
- bioinformatics4
- Bioinformatics3
- Gene Expression3
- RNA-Seq2
- ChIP-seq2
- HDRUK2
- RNASeq2
- Single Cell Genomics2
- Variant detection2
- next-generation sequencing2
- scRNAseq2
- R-programming1
- ABR1
- Bioconductor1
- Cross domain (cross-domain)1
- DNA & RNA (dna-rna)1
- Data analysis1
- Databases1
- Differential Expression1
- Droplet-based single-cell RNA library preparation1
- ELIXIR1
- Expression Atlas1
- Functional analysis1
- Galaxy Australia1
- Gene expression1
- Gene expression (gene-expression)1
- HCA data portal1
- High Throughput Sequencing Analysis1
- Human Cell Atlas Data Coordination Platform1
- Mapping1
- Molecular building blocks of life1
- NGS1
- Next generation sequencing data analysis1
- Nextflow1
- Pathway analysis1
- Quality Control1
- R software1
- RNA sequencing1
- RNAseq1
- Sequence Analysis1
- Seurat1
- Single Cell technologies1
- Single cell1
- Single-cell transcriptomics1
- TtT, Train the Trainer, Educational psychology, cognitive science, teaching practices 1
- VLSCI1
- Workflows1
- nf-core1
- omics1
- python1
- scRNA-seq1
- single cell RNA-seq analysis1
- tidyverse1
- Show N_FILTERS more
-
-
-
Scientific topic
- Bioinformatics1085
- Genome annotation289
- Exomes286
- Genomes286
- Genomics286
- Personal genomics286
- Synthetic genomics286
- Viral genomics286
- Whole genomes286
- Biological modelling229
- Biological system modelling229
- Systems biology229
- Systems modelling229
- Biomedical research188
- Clinical medicine188
- Experimental medicine188
- General medicine188
- Internal medicine188
- Medicine188
- Data visualisation184
- Data rendering177
- Bottom-up proteomics145
- Discovery proteomics145
- MS-based targeted proteomics145
- MS-based untargeted proteomics145
- Metaproteomics145
- Peptide identification145
- Protein and peptide identification145
- Proteomics145
- Quantitative proteomics145
- Targeted proteomics145
- Top-down proteomics145
- Data management122
- Metadata management122
- Research data management (RDM)122
- Data mining113
- Pattern recognition113
- Aerobiology99
- Behavioural biology99
- Biological rhythms99
- Biological science99
- Biology99
- Chronobiology99
- Cryobiology99
- Reproductive biology99
- Comparative transcriptomics90
- Transcriptome90
- Transcriptomics90
- Exometabolomics68
- LC-MS-based metabolomics68
- MS-based metabolomics68
- MS-based targeted metabolomics68
- MS-based untargeted metabolomics68
- Mass spectrometry-based metabolomics68
- Metabolites68
- Metabolome68
- Metabolomics68
- Metabonomics68
- NMR-based metabolomics68
- Functional genomics65
- Cloud computing60
- Computer science60
- HPC60
- High performance computing60
- High-performance computing60
- Computational pharmacology57
- Pharmacoinformatics57
- Pharmacology57
- Active learning51
- Ensembl learning51
- Immunology51
- Kernel methods51
- Knowledge representation51
- Machine learning51
- Neural networks51
- Recommender system51
- Reinforcement learning51
- Supervised learning51
- Unsupervised learning51
- Biomathematics47
- Computational biology47
- Mathematical biology47
- Theoretical biology47
- Pipelines40
- RNA-Seq analysis40
- Software integration40
- Tool integration40
- Tool interoperability40
- Workflows40
- Data archival37
- Data archiving37
- Data curation37
- Data curation and archival37
- Data preservation37
- Database curation37
- Research data archiving37
- High-throughput sequencing35
- Chromosome walking34
- Clone verification34
- DNA-Seq34
- Show N_FILTERS more
-
-
-
Operation
- Data visualisation3
- Molecular visualisation3
- Plotting3
- Rendering3
- Visualisation3
- Consensus-based sequence alignment2
- Constrained sequence alignment2
- Data analysis2
- Expression analysis2
- Expression data analysis2
- Gene expression analysis2
- Gene expression data analysis2
- Gene expression regulation analysis2
- Genetic variation analysis2
- Genetic variation annotation2
- Metagenomic inference2
- Microarray data analysis2
- Multiple sequence alignment (constrained)2
- Oligonucleotide alignment2
- Oligonucleotide alignment construction2
- Oligonucleotide alignment generation2
- Oligonucleotide mapping2
- Peak calling2
- Peak-pair calling2
- Protein binding peak detection2
- Protein expression analysis2
- Read alignment2
- Read mapping2
- Read pre-processing2
- Sequence alignment2
- Sequence alignment (constrained)2
- Sequence alignment construction2
- Sequence alignment generation2
- Sequence read pre-processing2
- Sequence variation analysis2
- Short oligonucleotide alignment2
- Short read alignment2
- Short read mapping2
- Short sequence read mapping2
- Transcript variant analysis2
- Variant analysis2
- Allele calling1
- Biological pathway analysis1
- Biological pathway modelling1
- Biological pathway prediction1
- Differential expression analysis1
- Differential gene analysis1
- Differential gene expression analysis1
- Differential gene expression profiling1
- Differentially expressed gene identification1
- Exome variant detection1
- Functional clustering1
- Functional pathway analysis1
- Functional sequence clustering1
- Genome variant detection1
- Germ line variant calling1
- Mutation detection1
- Pathway analysis1
- Pathway comparison1
- Pathway modelling1
- Pathway prediction1
- Pathway simulation1
- Somatic variant calling1
- Variant calling1
- Variant mapping1
- de novo mutation detection1
- Show N_FILTERS more
-
-
-
Event type
- Workshops and courses32
- Show N_FILTERS more
-
-
-
Venue
- European Bioinformatics Institute, Hinxton4
- Craik-Marshall Building2
- Earlham Institute (EI), Colney Lane2
- Via Nizza, 522
- Arts West North Wing Room 355 Professors Walk University of Melbourne Carlton, VIC 30531
- Campus di Fisciano, Università degli Studi di Salerno, Via Giovanni Paolo II, n. 1321
- Campus di Fisciano, Università di Salerno1
- Computer Room (aula Calcolo) Department of Biosciences, University of Milan, Via Celoria 261
- Feinberg Room B1
- Instituto de Biología Agrícola de Mendoza / Institute of Agricultural biology (IBAM), Almirante Brown 500, Chacras de Coria1
- Lab-14, VLSCI1
- Leuven - Campus Gasthuisberg, Herestraat 491
- Ole-Johan Dahls hus, 23B, Gaustadalléen1
- Southbank campus of Griffith University1
- Station Biologique De Roscoff1
- Station Biologique De Roscoff, Place Georges Teissier1
- Show N_FILTERS more
-
-
-
Target audience
- post-docs3
- Cette formation est destinée aux biologistes (ingénieurs, doctorants, chercheurs, enseignants-chercheurs, praticiens…) confrontés à l’analyse de données NGS, et qui ne disposent pas des compétences bioinformatiques suffisantes.2
- Graduate students2
- Institutions and other external Institutions or individuals2
- PhD students2
- Postdocs and Staff members from the University of Cambridge2
- Anyone who wants to become a teacher / trainer or a better one1
- Beginners1
- Early Career Researchers (ECRs)1
- Job seeker1
- Life Science Researchers1
- PhD Students1
- PhD Students or young researchers in molecular biology and/or genetics with little or no background in bioinformatics. 1
- PhD students and young researchers in the life science and computational biology field who are planning to use RNA-seq data and are looking for the best practices to analyze these types of data1
- Small and Medium-sized Enterprises (SMEs)1
- This course is aimed at life science researchers wanting to learn more about processing RNA-Seq data and later downstream analysis. It will help those wanting a basic introduction to handling RNA-Seq data, guiding them through several common approaches that can be applied to their own datasets. It features taught and practical sessions that cover how to interpret gene expression data and learn more about the biological significance of certain results. 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 from Masters-level upwards within Latin America who are working with and/or generating their own plant genomic and transcriptomic datasets. Prerequisites: Some basic computational or previous bioinformatics experience is required for this workshop, particularly using the UNIX operating system (basic command line skills) and R. You may find the resources below useful: 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 Important: All participants must bring a laptop for the course. We will use a virtual machine (VM) provided by instructors for the course practical sessions. All laptops must be of 64-bit architecture with any Operating System and have at least 60 GB free space. Please also note: this course will be taught in Spanish, however the trainers are fluent in English and can offer language support where feasible. A number of travel fellowships are available for this course - early-stage researchers and researchers from underrepresented groups are especially encouraged to apply for CABANA travel fellowships. You can apply for travel fellowships via the course application form.1
- This course is aimed at researchers who are generating, planning on generating, or working with single cell RNA sequencing data. Prerequisites Participants will be using a Galaxy resource in-depth. Participants may also be asked to do brief coding in R. Please ensure that you complete the free tutorials before you attend the course: Introduction to Galaxy: https://galaxyproject.org/tutorials/g101/ Basic R concept tutorials: www.r-tutor.com/r-introduction There are other tutorials here, although they are not required: https://galaxyproject.org/learn/1
- This course is aimed at researchers who are generating, planning on generating, or working with single cell RNA sequencing data. Prerequisites Participants will be using a Galaxy resource in-depth. Participants may also be asked to do brief coding in R. Please ensure that you complete the free tutorials before you attend the course: Introduction to Galaxy: https://galaxyproject.org/tutorials/g101/ Basic R concept tutorials: www.r-tutor.com/r-introduction There are other tutorials here, although they are not required: https://galaxyproject.org/learn/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 Researchers1
- bioinformaticians1
- biologists1
- teachers / trainers1
- Show N_FILTERS more
-
- Only show online events
- Hide past events
- Hide disabled events