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Content provider
- University of Cambridge Bioinformatics Training78
- iAnn4
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Keyword
- HDRUK78
- Neurobiology1
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Scientific topic
- Behavioural biology
- Bioinformatics799
- Genome annotation238
- Exomes235
- Genomes235
- Genomics235
- Personal genomics235
- Synthetic genomics235
- Viral genomics235
- Whole genomes235
- Biological modelling231
- Biological system modelling231
- Systems biology231
- Systems modelling231
- Biomedical research194
- Clinical medicine194
- Experimental medicine194
- General medicine194
- Internal medicine194
- Medicine194
- Bottom-up proteomics138
- Discovery proteomics138
- MS-based targeted proteomics138
- MS-based untargeted proteomics138
- Metaproteomics138
- Peptide identification138
- Protein and peptide identification138
- Proteomics138
- Quantitative proteomics138
- Targeted proteomics138
- Top-down proteomics138
- Data visualisation116
- Data rendering109
- Aerobiology82
- Biological rhythms82
- Biological science82
- Biology82
- Chronobiology82
- Cryobiology82
- Reproductive biology82
- Data mining75
- Pattern recognition75
- Comparative transcriptomics62
- Transcriptome62
- Transcriptomics62
- Computational pharmacology60
- Pharmacoinformatics60
- Pharmacology60
- Exometabolomics56
- LC-MS-based metabolomics56
- MS-based metabolomics56
- MS-based targeted metabolomics56
- MS-based untargeted metabolomics56
- Mass spectrometry-based metabolomics56
- Metabolites56
- Metabolome56
- Metabolomics56
- Metabonomics56
- NMR-based metabolomics56
- Immunology49
- Functional genomics43
- Data management34
- Metadata management34
- Research data management (RDM)34
- Active learning31
- Ensembl learning31
- Kernel methods31
- Knowledge representation31
- Machine learning31
- Neural networks31
- Recommender system31
- Reinforcement learning31
- Supervised learning31
- Unsupervised learning31
- Biomathematics29
- Computational biology29
- Disease29
- Epigenomics29
- Mathematical biology29
- Pathology29
- Theoretical biology29
- Protein bioinformatics27
- Protein databases27
- Protein informatics27
- Proteins27
- Metagenomics25
- Shotgun metagenomics25
- Protein structure24
- Bioimaging21
- Biological imaging21
- Cloud computing20
- Computer science20
- HPC20
- High performance computing20
- High-performance computing20
- Antimicrobial stewardship19
- Electrophysiology19
- Medical microbiology19
- Microbial genetics19
- Microbial physiology19
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Target audience
- Graduate students78
- Institutions and other external Institutions or individuals78
- Postdocs and Staff members from the University of Cambridge78
- Existing R users who are not familiar with dplyr and ggplot28
- Those with programming experience in other languages that want to know what R can offer them8
- The course is targeted to either proteomics practitioners or data analysts/bioinformaticians that would like to learn how to use R to analyse proteomics data. Familiarity with mass spectrometry or proteomics in general is desirable1
- The tutorial will be at an introductory level1
- The tutorial will be of interest to computational biologists who use1
- This is aimed for life scientists with little or no experience in long-read sequencing that are looking at implementing these approaches in their research.1
- but not essential as we will walk through a MS typical experiment and data as part of learning about the tools.1
- but will also describe current research directions and challenges that will be of broad interest to researchers in computational biology.1
- produce or analyse large structured datasets.1
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Eligibility
- First come first served4
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