Training materials
Scientific topics: Simulation experiment
and Target audience: Life Science Researchers
and Include archived: true
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Scientific topic
- Simulation experiment
- Data management9
- Metadata management9
- Research data management (RDM)9
- Cloud computing3
- Computer science3
- HPC3
- High performance computing3
- High-performance computing3
- Bioinformatics2
- Active learning1
- Antimicrobial stewardship1
- Bayesian methods1
- Biological modelling1
- Biological system modelling1
- Biomathematics1
- Biostatistics1
- Botany1
- Chromosome walking1
- Clone verification1
- Comparative genomics1
- Computational biology1
- DNA-Seq1
- DNase-Seq1
- Data analysis1
- Data architecture1
- Data architecture, analysis and design1
- Data design1
- Descriptive statistics1
- Ensembl learning1
- Epidemiology1
- Evolution1
- Evolutionary biology1
- Exomes1
- Functional genomics1
- Gaussian processes1
- Genome annotation1
- Genomes1
- Genomics1
- Genotype1
- Genotype and phenotype1
- Genotype and phenotype resources1
- Genotype-phenotype1
- Genotype-phenotype analysis1
- Genotyping1
- High throughput sequencing1
- High-throughput sequencing1
- Inferential statistics1
- Kernel methods1
- Knowledge representation1
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- Markov processes1
- Mathematical biology1
- Medical microbiology1
- Microbial genetics1
- Microbial physiology1
- Microbial surveillance1
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- Molecular infection biology1
- Molecular microbiology1
- Multivariate statistics1
- NGS1
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- Neural networks1
- Next gen sequencing1
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- Panels1
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- Phenotype1
- Phenotyping1
- Phylogenomics1
- Plant1
- Plant anatomy1
- Plant biology1
- Plant cell biology1
- Plant ecology1
- Plant genetics1
- Plant physiology1
- Plant science1
- Plants1
- Primer walking1
- Probabilistic graphical model1
- Probability1
- Public health1
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- Rare diseases1
- Recommender system1
- Reinforcement learning1
- Sanger sequencing1
- Sequencing1
- Statistics1
- Statistics and probability1
- Supervised learning1
- Synthetic genomics1
- Systems biology1
- Systems modelling1
- Targeted next-generation sequencing panels1
- Theoretical biology1
- Unsupervised learning1
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- Intermediate1
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- MIT License1
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Target audience
- Life Science Researchers
- Anyone interested in simulation of metabolic models, and in PerMedCoE tools and activities3
- Computational biologists3
- modelers3
- bioinformaticians1
- computational scientists1
- programmers1
- software developers, bioinformaticians1
- software engineers1
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