Training materials
Keywords: Data standards
and Target audience: PhD students
and Scientific topics: Genotype and phenotype
1 material found
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Scientific topic
- Genotype and phenotype
- Active learning1
- Applied ontology1
- Botany1
- Content management1
- Data analysis1
- Data architecture1
- Data architecture, analysis and design1
- Data clean-up1
- Data cleaning1
- Data design1
- Data integrity1
- Data management1
- Data quality1
- Data quality management1
- Database management1
- Document management1
- Ensembl learning1
- File management1
- Genotype1
- Genotype and phenotype resources1
- Genotype-phenotype1
- Genotype-phenotype analysis1
- Genotyping1
- Kernel methods1
- Knowledge representation1
- Machine learning1
- Metadata management1
- Neural networks1
- Ontologies1
- Ontology1
- Ontology and terminology1
- Ontology relations1
- Phenotype1
- Phenotyping1
- Plant1
- Plant anatomy1
- Plant biology1
- Plant cell biology1
- Plant ecology1
- Plant genetics1
- Plant physiology1
- Plant science1
- Plants1
- Recommender system1
- Record management1
- Reinforcement learning1
- Research data management (RDM)1
- Supervised learning1
- Terminology1
- Unsupervised learning1
- Upper ontology1
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- European Bioinformatics Institute (EBI)1
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Keyword
- Data standards
- IMPC2
- Biomedical data1
- CRISPR1
- DNA-protein interaction1
- EGA1
- Epigenetic modifications1
- Gene function1
- Genetic data1
- Histone modifications1
- International Mouse Phenotyping Consortium1
- Mammalian Phenotype Ontology1
- Microarray1
- Mouse knockouts1
- Mouse models1
- Mouse phenotypes1
- NGS1
- Next-generation sequencing1
- Phenotype1
- Python1
- RNA-protein interaction1
- Real-time PCR1
- Spatial transcriptomics1
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Difficulty level
- Not specified1
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Target audience
- PhD students
- Clinicians1
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