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Keyword
- Expression Atlas7
- Galaxy6
- RNA-Seq5
- Bioinformatics4
- Transcriptomics4
- Gene Expression3
- Transcriptome assembly3
- RNA-Seq2
- ABR2
- Cross domain (cross-domain)2
- DNA & RNA (dna-rna)2
- Data analysis2
- Droplet-based single-cell RNA library preparation2
- Ensembl Genomes2
- Gene expression (gene-expression)2
- Gene transcripts2
- HCA data portal2
- HDRUK2
- Human Cell Atlas Data Coordination Platform2
- Molecular building blocks of life2
- Network analysis2
- Pathway analysis2
- RNA-seq2
- Single cell2
- Single cell RNA-seq2
- Single-cell transcriptomics2
- Spatial mapping of cell types2
- VLSCI2
- bioinformatics2
- R-programming1
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- Bioconductor1
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- COVID-191
- COVID-19 Data Portal1
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- Cell-level simulations1
- ChEBI1
- ChEMBL: Bioactive data for drug discovery1
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- Chemical biology (chemical-biology)1
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Scientific topic
- RNA-Seq analysis
- Bioinformatics1026
- Genome annotation287
- Exomes284
- Genomes284
- Genomics284
- Personal genomics284
- Synthetic genomics284
- Viral genomics284
- Whole genomes284
- Biological modelling236
- Biological system modelling236
- Systems biology236
- Systems modelling236
- Biomedical research194
- Clinical medicine194
- Experimental medicine194
- General medicine194
- Internal medicine194
- Medicine194
- Bottom-up proteomics144
- Discovery proteomics144
- MS-based targeted proteomics144
- MS-based untargeted proteomics144
- Metaproteomics144
- Peptide identification144
- Protein and peptide identification144
- Proteomics144
- Quantitative proteomics144
- Targeted proteomics144
- Top-down proteomics144
- Data visualisation133
- Data rendering126
- Data management93
- Metadata management93
- Research data management (RDM)93
- Aerobiology89
- Behavioural biology89
- Biological rhythms89
- Biological science89
- Biology89
- Chronobiology89
- Cryobiology89
- Reproductive biology89
- Data mining78
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- Comparative transcriptomics68
- Transcriptome68
- Transcriptomics68
- Exometabolomics67
- LC-MS-based metabolomics67
- MS-based metabolomics67
- MS-based targeted metabolomics67
- MS-based untargeted metabolomics67
- Mass spectrometry-based metabolomics67
- Metabolites67
- Metabolome67
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- Metabonomics67
- NMR-based metabolomics67
- Computational pharmacology61
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- Active learning46
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- Functional genomics44
- Epigenomics31
- Disease29
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- Pathology29
- Shotgun metagenomics29
- High-throughput sequencing28
- Pipelines28
- Protein databases28
- Software integration28
- Tool integration28
- Tool interoperability28
- Workflows28
- Chromosome walking27
- Clone verification27
- DNA-Seq27
- DNase-Seq27
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Operation
- Data analysis2
- Biological pathway analysis1
- Biological pathway modelling1
- Biological pathway prediction1
- Data visualisation1
- Functional clustering1
- Functional pathway analysis1
- Functional sequence clustering1
- Molecular visualisation1
- Pathway analysis1
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- Pathway modelling1
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Venue
- European Bioinformatics Institute, Hinxton6
- 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
- EMBL-EBI, EMBL EBI1
- Feinberg Room B1
- Instituto de Biología Agrícola de Mendoza / Institute of Agricultural biology (IBAM), Almirante Brown 500, Chacras de Coria1
- LAB-141
- Lab-14, VLSCI1
- Ole-Johan Dahls hus, 23B, Gaustadalléen1
- Southbank campus of Griffith University1
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Target audience
- post-docs3
- 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
- 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
- Plant research1
- Wet-lab Researchers1
- bioinformaticians1
- biologists1
- teachers / trainers1
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