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- INB: Spanish National Bioinformatics Institute1
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Keyword
- Artificial Intelligence1
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- Evolutinary genomics1
- Genomics1
- HPC1
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- Population Genomics1
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Scientific topic
- Data management15
- Metadata management15
- Research data management (RDM)15
- Bioinformatics14
- Cloud computing11
- Computer science11
- HPC11
- High performance computing11
- High-performance computing11
- Exomes10
- Genome annotation10
- Genomes10
- Genomics10
- Personal genomics10
- Synthetic genomics10
- Viral genomics10
- Whole genomes10
- Biological sequences4
- Chromosome walking4
- Clone verification4
- DNA-Seq4
- DNase-Seq4
- High throughput sequencing4
- High-throughput sequencing4
- NGS4
- NGS data analysis4
- Next gen sequencing4
- Next generation sequencing4
- Panels4
- Primer walking4
- Sanger sequencing4
- Sequence analysis4
- Sequence databases4
- Sequencing4
- Targeted next-generation sequencing panels4
- Population genomics3
- Active learning2
- Bayesian methods2
- Biostatistics2
- Comparative modelling2
- Data archival2
- Data archiving2
- Data curation2
- Data curation and archival2
- Data preservation2
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- Database curation2
- Descriptive statistics2
- Docking2
- Ensembl learning2
- Exometabolomics2
- Gaussian processes2
- Homology modeling2
- Homology modelling2
- Inferential statistics2
- Kernel methods2
- Knowledge representation2
- LC-MS-based metabolomics2
- MS-based metabolomics2
- MS-based targeted metabolomics2
- MS-based untargeted metabolomics2
- Machine learning2
- Marine biology2
- Markov processes2
- Mass spectrometry-based metabolomics2
- Metabolites2
- Metabolome2
- Metabolomics2
- Metabonomics2
- MicroRNA sequencing2
- Molecular docking2
- Molecular modelling2
- Multivariate statistics2
- NMR-based metabolomics2
- Neural networks2
- Probabilistic graphical model2
- Probability2
- RNA sequencing2
- RNA-Seq2
- RNA-Seq analysis2
- Recommender system2
- Reinforcement learning2
- Research data archiving2
- Small RNA sequencing2
- Small RNA-Seq2
- Small-Seq2
- Statistics2
- Statistics and probability2
- Supervised learning2
- Transcriptome profiling2
- Unsupervised learning2
- WTSS2
- Whole transcriptome shotgun sequencing2
- miRNA-seq2
- Aerobiology1
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- Meetings and conferences1
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Country
- Spain1
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Target audience
- PhD students
- Plant research2
- Computational biologists1
- Computer science1
- Graduate students1
- Institutions and other external Institutions or individuals1
- Postdocs and Staff members from the University of Cambridge1
- Postdoctoral students1
- Researchers1
- This course is intended for master and PhD students, post-docs and staff scientists familiar with different omics data technologies who are interested in applying machine learning to analyse these data. No prior knowledge of Machine Learning concepts and methods is expected nor required1
- biocurators1
- bioinformaticians1
- software developers, bioinformaticians1
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