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Content provider
- ELIXIR Portugal8
- BioData.pt6
- ELIXIR Slovenia5
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Keyword
- EeLP6
- eLearning6
- Data management plan4
- training4
- Data managment plan3
- life sciences3
- Assembly2
- Computer science2
- Genomics2
- Proteomics2
- Training2
- metabolic modelling, Genome, open-source software platform1
- Course design1
- Course development1
- Gadgets, software 1
- Integrative1
- Machine Learning, Introductory, Novice / Entry-level, Supervised learning, Unsupervised learning, Principal Component Analysis, K-means, Hierarchical Clustering, Decision Trees, Random Forest, Regression1
- Mass Spectroscopy1
- Teaching1
- bioinformatics1
- data annotation1
- data management1
- data stewardship1
- genomics1
- high-performance computing1
- online learning1
- pedagogy1
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Scientific topic
- Data management7
- Metadata management7
- Research data management (RDM)5
- Cloud computing3
- Computer science3
- HPC3
- High performance computing3
- High-performance computing3
- Bioinformatics2
- Exomes2
- Genome annotation2
- Genomes2
- Genomics2
- Personal genomics2
- Synthetic genomics2
- Viral genomics2
- Whole genomes2
- Active learning1
- Bayesian methods1
- Biomathematics1
- Biostatistics1
- Computational biology1
- Data curation1
- Data provenance1
- Data submission, annotation, and curation1
- Database curation1
- Descriptive statistics1
- Ensembl learning1
- FAIR data1
- Findable, accessible, interoperable, reusable data1
- Gaussian processes1
- Inferential statistics1
- Kernel methods1
- Knowledge representation1
- Machine learning1
- Markov processes1
- Mathematical biology1
- Multivariate statistics1
- Neural networks1
- Probabilistic graphical model1
- Probability1
- Proteogenomics1
- Recommender system1
- Reinforcement learning1
- Statistics1
- Statistics and probability1
- Supervised learning1
- Theoretical biology1
- Unsupervised learning1
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Venue
- Instituto Gulbenkian de Ciência3
- Instituto Gulbenkian de Ciência (IGC), 6, Rua Quinta Grande2
- University of Ljubljana, Faculty of Medicine2
- University of Minho - Campus of Gualtar, Rua da Universidade2
- Champalimaud Foundation, Avenida Brasília1
- Cirad, 389, Avenue Agropolis1
- Escuela Técnica Superior de Ingeniería Informática, 35, Bulevar Louis Pasteur1
- ITQB NOVA, Avenida da República1
- Instituto Gulbenkian de Ciência, Oeiras, PT1
- Instituto de Medicina Molecular (IMM), Avenida Professor Egas Moniz1
- Online and F2F (See details in training documentation)1
- R. Q.ta Grande 6, 6, Rua Quinta Grande1
- Rua da Quinta Grande, 61
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Organizer
- Pedro Fernandes6
- BioData.pt4
- ELIXIR Slovenia2
- BioData.pt | ELIXIR Portugal1
- BioData.pt, ITQB NOVA1
- BioData.pt, iMM - Instituto de Medicina Molecular João Lobo Antunes1
- Biodata.pt; Congento; RNEM - Portuguese Mass Spectrometry Network1
- ELIXIR PT, Instituto Gulbenkian1
- ELIXIR-BE, ELIXIR-FR, ELIXIR-NO, ELIXIR-PT, ELIXIR-SE, ELIXIR-SI1
- Escuela Técnica Superior de Ingeniería Informática1
- Instituto Gulbenkian, ELIXIR Portugal, GOBLET1
- Pedro L Fernandes1
- Universidade do Minho1
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Target audience
- PhD students11
- Life Science Researchers7
- Researchers7
- Master students6
- Technicians6
- life scientists5
- PhD Students2
- post-doctoral researchers and principle investigators working in wet-lab biology. Participants who are looking for a basic introduction to the bioinformatics resources offered by the EMBL-EBI and want to know more about accessing biological data and tools.2
- Researchers in Life Sciences1
- Biologists and bioinformaticians who are dealing with high-throughput gene expression data or other high-throughput data and would like to learn state-of-the-art methods for mining and analysing such data.1
- Biologists, Genomicists, Computer Scientists1
- Research Assistants and Research Associates1
- Scientists1
- bioinformaticians1
- computational and statistical techniques are used to identify and validate the causal links between targets1
- everyone who is interested in learning to use metabolic modelling in their research, using user-friendly tools. No programming skills are required.1
- post-docs1
- students1
- teachers1
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