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- University of Cambridge Bioinformatics Training75
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Keyword
- HDRUK75
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Scientific topic
- Pattern recognition
- 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
- Reproductive biology82
- Data mining75
- 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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Event type
- Workshops and courses75
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Country
- United Kingdom75
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Target audience
- Institutions and other external Institutions or individuals75
- Postdocs and Staff members from the University of Cambridge75
- Graduate students74
- This is aimed at life scientists with little or no experience in machine learning and that are looking at implementing these approaches in their research.13
- Researchers who are applying or planning to apply image analysis in their research4
- Researchers who want to extract quantitative information from microscopy images4
- This introductory course is aimed at biologists with little or no experience in machine learning.3
- The course is aimed primarily at mid-career scientists – especially those whose formal education likely included statistics2
- but who have not perhaps put this into practice since.2
- <span style="color:#FF0000">Please note that all participants attending this course will be charged a registration fee. <span style="color:#0000FF"> Members of Industry to pay 575.00 GBP. </span style> <span style="color:#0000FF">All Members of the University of Cambridge1
- Affiliated Institutions and other academic participants from External Institutions and Charitable Organizations to pay 250.00 GBP. </span style> <span style="color:#FF0000">A booking will only be approved and confirmed once the fee has been paid in full.</span style>1
- BioImage Analysts with some experience of basic microscopy image analysis1
- Biophysicists1
- Cell Biologists1
- The course is aimed at biologists interested in microbiology1
- The course is open to Graduate students1
- The handson component is aimed at novice to intermediate users who are seeking detailed guidance with GATK and related tools.1
- The lecture based component of the workshop is aimed at a mixed audience of people who are new to the topic of variant discovery or to GATK1
- This course is appropriate for researchers who are relatively proficient with computers but maybe not had the time or resources available to become programmers.1
- This course may be of interest to physical scientists looking to develop their knowledge of Python coding in the context of bioimage analysis1
- analysis of complex microbiomes and antimicrobial resistance.1
- or who are already GATK users seeking to improve their understanding of and proficiency with the tools.1
- prokaryotic genomics1
- seeking an introductory course into the tools1
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Eligibility
- First come first served8
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