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Content provider
- European Bioinformatics Institute (EBI)21
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Keyword
- Expression Atlas6
- RNA-Seq5
- Transcriptome assembly5
- Transcriptomics5
- Gene transcripts4
- spatial transcriptomics4
- Galaxy3
- Droplet-based single-cell RNA library preparation2
- Network analysis2
- Spatial mapping of cell types2
- spatial data2
- transcriptomics2
- Cross domain (cross-domain)1
- DNA & RNA (dna-rna)1
- Dimensionality reduction1
- Ensembl Genomes1
- Galaxy Europe1
- Gene Transcripts1
- Gene expression (gene-expression)1
- HCA data portal1
- Human Cell Atlas Data Coordination Platform1
- Molecular building blocks of life1
- Pipeline implementation1
- Single cell1
- Single cell RNA-seq1
- Single cell expression atlas1
- Single-cell RNA library preparation1
- Single-cell transcriptomics1
- data visualisation1
- dimensionality reduction1
- galaxy project1
- single cell RNA-seq analysis1
- single cell expression atlas1
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Scientific topic
- RNA-Seq analysis
- Bioinformatics49
- Genome annotation34
- Exomes30
- Genomes30
- Genomics30
- Personal genomics30
- Synthetic genomics30
- Viral genomics30
- Whole genomes30
- Protein function analysis28
- Protein function prediction28
- Active learning26
- Ensembl learning26
- Kernel methods26
- Knowledge representation26
- Machine learning26
- Neural networks26
- Protein bioinformatics26
- Protein databases26
- Protein informatics26
- Proteins26
- Recommender system26
- Reinforcement learning26
- Supervised learning26
- Unsupervised learning26
- Biomathematics23
- Computational biology23
- Mathematical biology23
- Theoretical biology23
- Biological modelling22
- Biological system modelling22
- Protein structure22
- Systems biology22
- Systems modelling22
- Comparative transcriptomics20
- Function analysis20
- Functional analysis20
- Protein structures20
- Transcriptome20
- Transcriptomics20
- Molecular diagnostics18
- Personalised medicine18
- Precision medicine18
- Data archival16
- Data archiving16
- Data curation16
- Data curation and archival16
- Data management16
- Data preservation16
- Database curation16
- Metabolic network modelling16
- Metabolic network reconstruction16
- Metabolic network simulation16
- Metabolic pathway modelling16
- Metabolic pathway reconstruction16
- Metabolic pathway simulation16
- Metabolic reconstruction16
- Metadata management16
- Research data archiving16
- Research data management (RDM)16
- Structural assignment16
- Structural biology16
- Structural determination16
- Structure determination16
- Amino acid sequence15
- Amino acid sequences15
- Bioimaging15
- Biological imaging15
- Biological models15
- Biological networks15
- Biological pathways15
- Cellular process pathways15
- Disease pathways15
- Environmental information processing pathways15
- Gene regulatory networks15
- Genetic information processing pathways15
- Interactions15
- Interactome15
- Metabolic pathways15
- Metagenomics15
- Molecular interactions15
- Molecular interactions, pathways and networks15
- Networks15
- Omics15
- Pathways15
- Protein sequence15
- Protein sequences15
- Shotgun metagenomics15
- Signal transduction pathways15
- Signaling pathways15
- Antimicrobial stewardship14
- Chromosome walking14
- Clone verification14
- Community analysis14
- DNA-Seq14
- DNase-Seq14
- Data visualisation14
- Environmental microbiology14
- High throughput sequencing14
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Event type
- Workshops and courses21
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Target audience
- 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
- This course is aimed at researchers with little to no experience in big data analysis and who are generating, planning on generating, or working with single cell RNA sequencing data.1
- This course is aimed at researchers with little-to-no experience in big data analysis and who are generating, planning on generating, or working with single-cell RNA sequencing data.1
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Instructor
- Wendi Bacon6
- Pablo Moreno5
- Zhichao Miao4
- Jonathan Manning3
- Kerstin Meyer3
- Kristina Kirschner3
- Nancy George3
- Silvie Fexova3
- Tamir Chandra3
- Zinaida Perova3
- Irene Papatheodorou2
- Mehmet Tekman2
- Simone Webb2
- Alexandra Holinski1
- Alfonso Munoz-Pomer Fuentes1
- Andres Rabinovich1
- Andrew Stubbs1
- Anil Shantilal Thanki1
- Anton Petrov1
- Ariel Chernomoretz1
- Asier Gonzalez1
- Blake Sweeney1
- Brett McClintock1
- Carlos Talavera-Lopez1
- Danielle Welter1
- Denise Carvalho-Silva1
- Denye Ogeh1
- Graeme Tyson1
- Iguaracy Pinheiro de Sousa1
- Iris Diana Yu1
- Jamie Allen1
- Jon Manning1
- Jongeun Park1
- Julia Jakiela1
- Kostas Billis1
- Leanne Haggerty1
- Liis Kolberg1
- Mallory Freeberg1
- Malwina Prater1
- Marisa Loach1
- Maximilian Haeussler1
- Maximiliano Beckel1
- Maximo Rivarola1
- Mirjana Efremova1
- Roser Vento-Tormo1
- Sarah Morgan1
- Scooter Morris1
- Sergio Gonzalez - INTA Castelar1
- Simon Andrews1
- Suhaib Mohammed1
- Tallulah Andrews1
- Thawfeek Mohamed Varusai1
- Tom Hancocks1
- Vladimir Uzun1
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