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Content provider
- ELIXIR Portugal21
- ELIXIR Slovenia1
- NanoCommons1
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Keyword
- Data managment plan3
- Proteomics3
- Bioinformatics2
- EeLP2
- Genomics2
- eLearning2
- Assembly1
- Statistics1
- metabolic modelling, Genome, open-source software platform1
- #bioinformatics hashtag#pangenomics hashtag#data hashtag#analysis hashtag#genomicdata hashtag#genomics hashtag#course1
- Biodata, Bioinformatics, Biodata1
- Clinical oncology1
- Computational Pangenomics1
- Data analysis1
- Data management plan1
- Drug Targetting1
- Gadgets, software 1
- General Linear Models1
- 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
- Metagenomics1
- Teaching1
- Training1
- Variant calling1
- advanced cellular models1
- adverse outcome pathway1
- bioinformatics1
- cancer1
- chemotherapy1
- data FAIRness1
- data annotation1
- data management1
- data stewardship1
- data visualization1
- drug prioritization1
- gene panels1
- genomics1
- in silico prediction1
- life sciences1
- molecular initiating events1
- nanosafety assessment1
- protein corona formation1
- training1
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Scientific topic
- Bioinformatics4
- Data management4
- Exomes4
- Genome annotation4
- Genomes4
- Genomics4
- Metadata management4
- Personal genomics4
- Synthetic genomics4
- Viral genomics4
- Whole genomes4
- Bayesian methods2
- Biostatistics2
- Cancer2
- Cancer biology2
- Descriptive statistics2
- Gaussian processes2
- Inferential statistics2
- Markov processes2
- Multivariate statistics2
- Neoplasm2
- Neoplasms2
- Oncology2
- Probabilistic graphical model2
- Probability2
- Statistics2
- Statistics and probability2
- Active learning1
- Biomarkers1
- Biome sequencing1
- Biotherapeutics1
- Data curation1
- Data provenance1
- Data submission, annotation, and curation1
- Database curation1
- Diagnostic markers1
- Ensembl learning1
- FAIR data1
- Findable, accessible, interoperable, reusable data1
- Kernel methods1
- Knowledge representation1
- Machine learning1
- Metagenomic sequencing1
- Metagenomics1
- Neural networks1
- Proteogenomics1
- Recommender system1
- Reinforcement learning1
- Shotgun metagenomic sequencing1
- Shotgun metagenomics1
- Supervised learning1
- Unsupervised learning1
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Operation
- Allele calling1
- Classification1
- Clustering1
- Data handling1
- Empirical Bayes1
- Exome variant detection1
- File handling1
- File processing1
- Genome variant detection1
- Germ line variant calling1
- Mathematical modelling1
- Modelling and simulation1
- Mutation detection1
- Principal component analysis1
- Processing1
- Report handling1
- Somatic variant calling1
- Statistical inference1
- Statistical modelling1
- Utility operation1
- Variant calling1
- Variant mapping1
- Variant pattern analysis1
- Variant prioritisation1
- de novo mutation detection1
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Venue
- Instituto Gulbenkian de Ciência7
- Instituto Gulbenkian de Ciência (IGC), 6, Rua Quinta Grande6
- R. Q.ta Grande 6, 6, Rua Quinta Grande2
- University of Minho - Campus of Gualtar, Rua da Universidade2
- Champalimaud Foundation, Avenida Brasília1
- Faro1
- ITQB NOVA, Avenida da República1
- Instituto Gulbenkian de Ciencia1
- Instituto de Medicina Molecular (IMM), Avenida Professor Egas Moniz1
- International Nanotechnology Laboratories - INL1
- Online and F2F (See details in training documentation)1
- Rua da Quinta Grande, 61
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Organizer
- Pedro Fernandes10
- BioData.pt2
- BioData.pt | ELIXIR Portugal1
- Biodata.pt1
- Biodata.pt; Congento; RNEM - Portuguese Mass Spectrometry Network1
- ELIXIR PT, Instituto Gulbenkian1
- GTPB - IGC1
- Instituto Gulbenkian, ELIXIR Portugal, GOBLET1
- Rita Castilho, Center for Marine Sciences1
- The Gulbenkian Training Programme in Bioinformatics1
- The Gulbenkian Training Programme in Bioinformatics, Biodata.pt - Elixir's portuguese node of the european project1
- The Gulbenkian Training Programme in Bioinformatics, Biodata.pt - Elixir's portuguese node of the european project1
- Universidade do Minho1
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Target audience
- Life Science Researchers7
- PhD students5
- Researchers4
- Master students3
- Technicians3
- bioinformaticians3
- 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.2
- Biologists, Genomicists, Computer Scientists2
- PhD Students2
- post-docs2
- Institutions and other external Institutions or individuals1
- Researchers in Life Sciences1
- health professionals1
- studies human diseases or developmental biology1
- Bioinformaticians1
- Bioinformaticians and wet-lab biologists who can program in Perl.1
- Biologists and bioinformaticians. The course will be of particular interest to researchers investigating organisms without a reference genome or populations featuring high levels of genetic diversity.1
- Biomedical researchers1
- Clinical Scientists1
- Drug resistance1
- Industry1
- Microbiologists1
- Postdoctoral Researchers1
- Scientists1
- This course is oriented towards biologists and bioinformaticians. The course will be of particular interest to researchers investigating organisms without a reference genome or populations featuring high levels of genetic diversity.1
- This training course is aimed at researchers who are not expert in proteomics and want to integrate quantitative proteomics results into wider biomedical experiments.1
- biocurators1
- biology and bioinformatics sophomore undergraduates1
- 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
- healthcare professionals 1
- life scientists1
- oncologists1
- plant researchers1
- 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.1
- software developers, bioinformaticians1
- students1
- teachers1
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