Training materials
Scientific topics: Recommender system
and Keywords: Structures (structures)
and Include archived: true
1 material found
- Home
- Materials
Filters
Sort
-
-
Filter Clear filters
-
-
Scientific topic
- Recommender system
- Active learning1
- DNA structure prediction1
- Ensembl learning1
- Kernel methods1
- Knowledge representation1
- Machine learning1
- Neural networks1
- Nucleic acid design1
- Nucleic acid folding1
- Nucleic acid structure prediction1
- Protein fold recognition1
- Protein structure prediction1
- RNA structure prediction1
- Reinforcement learning1
- Structural assignment1
- Structural biology1
- Structural determination1
- Structure determination1
- Structure prediction1
- Supervised learning1
- Unsupervised learning1
- Show N_FILTERS more
-
-
-
Content provider
- ELIXIR: The Czech Republic Node1
- Show N_FILTERS more
-
-
-
Keyword
- Structures (structures)
- Machine learning52
- Python14
- R13
- Statistics12
- Data science10
- Artificial intelligence6
- General5
- AlphaFold Database (13181)3
- Data visualization2
- Machine Learning2
- Proteomics2
- Reproducibility2
- Single-cell sequencing2
- Snakemake2
- Structure prediction2
- Transcriptomics2
- ATAC-seq1
- Alphafold1
- Bioinformatics1
- ChIP-seq1
- Coding1
- Comparative genomics1
- Computational Biology1
- Computer Science1
- Data Analysis1
- Data Science1
- Data management1
- Data standards1
- Deep Learning1
- Deep learning1
- EeLP1
- Epigenetics1
- FAIR data1
- Galaxy1
- Genome annotation1
- Genome assembly1
- Genomics1
- High performance computing1
- Julia1
- Long read sequencing1
- Metabolomics1
- Metagenomics1
- Microbiology1
- Next generation sequencing1
- Pathways and Networks1
- Programming1
- RNA-seq1
- Spatial transcriptomics1
- Unix/Linux1
- Variant analysis1
- Version control1
- Workflows1
- biostatistics1
- eLearning1
- machine learning1
- protein-3D-structure1
- Show N_FILTERS more
-
-
-
Difficulty level
- Not specified1
- Show N_FILTERS more
-
-
-
Status
- Active1
- Show N_FILTERS more
-
- Hide archived materials
