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Scientific topics: Multivariate statistics
and Resource type: e-learning
33 e-learning materials found
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Scientific topic
- Multivariate statistics
- Algorithms66
- Computer programming66
- Data structures66
- Programming languages66
- Software development66
- Software engineering66
- Exomes46
- Genome annotation46
- Genomes46
- Genomics46
- Personal genomics46
- Synthetic genomics46
- Viral genomics46
- Whole genomes46
- Bottom-up proteomics44
- Discovery proteomics44
- MS-based targeted proteomics44
- MS-based untargeted proteomics44
- Metaproteomics44
- Peptide identification44
- Protein and peptide identification44
- Proteomics44
- Quantitative proteomics44
- Targeted proteomics44
- Top-down proteomics44
- Bayesian methods33
- Biological sequences33
- Biostatistics33
- Descriptive statistics33
- Gaussian processes33
- Inferential statistics33
- Markov processes33
- Probabilistic graphical model33
- Probability33
- Sequence analysis33
- Sequence databases33
- Statistics33
- Statistics and probability33
- Computational ecology27
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- Antimicrobial stewardship25
- Comparative transcriptomics25
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- Microbiology25
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- Transcriptome25
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- Assembly23
- Community analysis23
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- Metagenomics23
- Microbial ecology23
- Microbiome23
- Molecular community analysis23
- Sequence assembly23
- Shotgun metagenomics23
- DNA variation22
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- Mutation22
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- Taxonomy15
- Biodiversity14
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- Diffraction experiment13
- Exometabolomics13
- Imaging13
- LC-MS-based metabolomics13
- MS-based metabolomics13
- MS-based targeted metabolomics13
- MS-based untargeted metabolomics13
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- Metabolites13
- Metabolome13
- Metabolomics13
- Metabonomics13
- Microscopy13
- Microscopy imaging13
- NMR-based metabolomics13
- Optical super resolution microscopy13
- Photonic force microscopy13
- Photonic microscopy13
- Bioinformatics10
- Protein bioinformatics10
- Protein databases10
- Protein informatics10
- Protein structure10
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Keyword
- Statistics and machine learning28
- ai-ml10
- elixir10
- jupyter-notebook9
- Large Language Model5
- interactive-tools4
- work-in-progress4
- deep-learning2
- jupyter-lab2
- machine-learning2
- statistics2
- Biostatistics1
- Digital Humanities1
- Machine learning1
- Open access1
- Pan-cancer1
- R1
- cancer biomarkers1
- dephosphorylation-site-prediction1
- fine-tuning1
- image-segmentation1
- microbial ecosystems1
- microbiome1
- oncogenes and tumor suppressor genes1
- protein-3D-structure1
- text mining1
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- Beginner19
- Intermediate12
- Not specified2
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Target audience
- Students29
- Clinicians2
- PhD students2
- biologists2
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Author
- Anup Kumar9
- Bérénice Batut6
- Raphael Mourad6
- Alireza Khanteymoori4
- Kaivan Kamali4
- Daniel Blankenberg2
- Fabio Cumbo2
- Fotis E. Psomopoulos2
- Janick Mathys2
- Ralf Gabriels2
- Simon Bray2
- Daniela Schneider1
- Dennis Lal group1
- Ekaterina Polkh1
- Marie Gramm1
- Marzia A Cremona1
- Stella Fragkouli1
- Vijay1
- Wandrille Duchemin1
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Contributor
- Saskia Hiltemann23
- Björn Grüning20
- Anup Kumar19
- Bérénice Batut15
- Helena Rasche15
- Martin Čech12
- Armin Dadras9
- Teresa Müller6
- Alireza Khanteymoori5
- Kaivan Kamali5
- Wandrille Duchemin5
- olisand5
- Fabio Cumbo3
- Gildas Le Corguillé2
- Michelle Terese Savage2
- Nate Coraor2
- qiagu2
- Anthony Bretaudeau1
- Bert Droesbeke1
- Daniel Blankenberg1
- Daniel Sobral1
- Daniela Schneider1
- Enis Afgan1
- Mélanie Petera1
- Niall Beard1
- Nicola Soranzo1
- Simon Bray1
- Stella Fragkouli1
- Vijay1
- dlal-group1
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