Training materials
Target audience: PhD students
and Scientific topics: Probabilistic graphical model
and Difficulty level: Intermediate
1 material found
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Scientific topic
- Probabilistic graphical model
- Active learning2
- Ensembl learning2
- Kernel methods2
- Knowledge representation2
- Machine learning2
- Neural networks2
- Recommender system2
- Reinforcement learning2
- Supervised learning2
- Unsupervised learning2
- Bayesian methods1
- Biostatistics1
- Bottom-up proteomics1
- Descriptive statistics1
- Discovery proteomics1
- Gaussian processes1
- Inferential statistics1
- MS-based targeted proteomics1
- MS-based untargeted proteomics1
- Markov processes1
- Metaproteomics1
- MicroRNA sequencing1
- Multivariate statistics1
- Omics1
- Peptide identification1
- Probability1
- Protein and peptide identification1
- Proteomics1
- Quantitative proteomics1
- RNA sequencing1
- RNA-Seq1
- RNA-Seq analysis1
- Rare diseases1
- Small RNA sequencing1
- Small RNA-Seq1
- Small-Seq1
- Statistics1
- Statistics and probability1
- Targeted proteomics1
- Top-down proteomics1
- Transcriptome profiling1
- WTSS1
- Whole transcriptome shotgun sequencing1
- miRNA-seq1
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Content provider
- UCLouvain Bioinformatics Platform1
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Difficulty level
- Intermediate
- Not specified2
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