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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
- Reproductive biology
- Bioinformatics799
- Genome annotation243
- Exomes240
- Genomes240
- Genomics240
- Personal genomics240
- Synthetic genomics240
- Viral genomics240
- Whole genomes240
- Biological modelling231
- Biological system modelling231
- Systems biology231
- Systems modelling231
- Biomedical research194
- Clinical medicine194
- Experimental medicine194
- General medicine194
- Internal medicine194
- Medicine194
- Bottom-up proteomics139
- Discovery proteomics139
- MS-based targeted proteomics139
- MS-based untargeted proteomics139
- Metaproteomics139
- Peptide identification139
- Protein and peptide identification139
- Proteomics139
- Quantitative proteomics139
- Targeted proteomics139
- Top-down proteomics139
- Data visualisation116
- Data rendering109
- Aerobiology82
- Behavioural biology82
- Biological rhythms82
- Biological science82
- Biology82
- Chronobiology82
- Cryobiology82
- 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 genomics44
- Data management41
- Metadata management41
- Research data management (RDM)41
- Active learning39
- Ensembl learning39
- Kernel methods39
- Knowledge representation39
- Machine learning39
- Neural networks39
- Recommender system39
- Reinforcement learning39
- Supervised learning39
- Unsupervised learning39
- Disease30
- Epigenomics30
- Pathology30
- Biomathematics29
- Computational biology29
- Mathematical biology29
- Theoretical biology29
- Metagenomics27
- Protein bioinformatics27
- Protein databases27
- Protein informatics27
- Proteins27
- Shotgun metagenomics27
- Bioimaging26
- Biological imaging26
- Protein structure24
- Antimicrobial stewardship22
- Medical microbiology22
- Microbial genetics22
- Microbial physiology22
- Microbial surveillance22
- Microbiological surveillance22
- Microbiology22
- Molecular infection biology22
- Molecular microbiology22
- Cloud computing20
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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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