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- University of Cambridge Bioinformatics Training110
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Keyword
- HDRUK110
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Scientific topic
- Data mining
- Bioinformatics363
- Data rendering147
- Data visualisation147
- Pattern recognition110
- Aerobiology86
- Behavioural biology86
- Biological rhythms86
- Biological science86
- Biology86
- Chronobiology86
- Cryobiology86
- Reproductive biology86
- Functional genomics55
- Comparative transcriptomics50
- Transcriptome50
- Transcriptomics50
- Active learning22
- Ensembl learning22
- Kernel methods22
- Knowledge representation22
- Machine learning22
- Neural networks22
- Recommender system22
- Reinforcement learning22
- Supervised learning22
- Unsupervised learning22
- Python18
- Python program18
- Python script18
- py18
- Coding RNA15
- EST15
- Exons15
- Fusion genes15
- Fusion transcripts15
- Gene features15
- Gene structure15
- Gene transcript features15
- Gene transcripts15
- Introns15
- PolyA signal15
- PolyA site15
- Signal peptide coding sequence15
- Transit peptide coding sequence15
- cDNA15
- mRNA15
- mRNA features15
- Bioimaging14
- Biological imaging14
- Phylogenetics14
- ChIP-exo12
- ChIP-seq12
- ChIP-sequencing12
- Chip Seq12
- Chip sequencing12
- Chip-sequencing12
- Exomes10
- Genome annotation10
- Genomes10
- Genomics10
- Personal genomics10
- Synthetic genomics10
- Viral genomics10
- Whole genomes10
- DNA methylation9
- Epigenetics9
- Epigenomics9
- Histone modification9
- Methylation profiles9
- Exometabolomics8
- LC-MS-based metabolomics8
- MS-based metabolomics8
- MS-based targeted metabolomics8
- MS-based untargeted metabolomics8
- Mass spectrometry-based metabolomics8
- Metabolites8
- Metabolome8
- Metabolomics8
- Metabonomics8
- NMR-based metabolomics8
- Bottom-up proteomics5
- Discovery proteomics5
- MS-based targeted proteomics5
- MS-based untargeted proteomics5
- Metaproteomics5
- Peptide identification5
- Protein and peptide identification5
- Protein structure5
- Protein structure analysis5
- Protein tertiary structure5
- Proteomics5
- Quantitative proteomics5
- Targeted proteomics5
- Top-down proteomics5
- AMR4
- Antibiotic resistance (ABR)4
- Antifungal resistance4
- Antimicrobial resistance4
- Antiprotozoal resistance4
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Event type
- Workshops and courses110
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Country
- United Kingdom110
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Target audience
- Graduate students92
- Institutions and other external Institutions or individuals90
- Postdocs and Staff members from the University of Cambridge90
- 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.16
- Everyone is welcome to attend the courses9
- please review the policies.9
- <span style="color:#FF0000">After you have booked a place7
- if you are unable to attend any of the live sessions and would like to work in your own time7
- including for registered university students.<span style="color:#FF0000">7
- please email the Team as Attendance will be taken on all courses. A charge is applied for non-attendance7
- Note that we will not cover specific topics in phylogenomics (whole-genome phylogenies) or bacterial genomics.5
- This course is aimed at researchers with no prior experience in phylogenetic analysis who would like an introduction to the foundations of building phylogenies from relatively small sequences (viral genomes and/or targeted regions of eukaryotic genomes).5
- Anyone who is using sequencing as part of their work and/or research.4
- Researchers who are applying or planning to apply image analysis in their research4
- Researchers who want to extract quantitative information from microscopy images4
- Institutions and other external institutions or individuals.3
- Postdocs and other Research Staff from the University of Cambridge3
- The course is aimed at biologists interested in microbiology3
- This introductory course is aimed at biologists with little or no experience in machine learning.3
- analysis of complex microbiomes and antimicrobial resistance.3
- prokaryotic genomics3
- The course is aimed primarily at mid-career scientists – especially those whose formal education likely included statistics2
- This course is aimed at researchers with no prior experience in the analysis of ChIP-seq data2
- 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 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
- or who are already GATK users seeking to improve their understanding of and proficiency with the tools.1
- seeking an introductory course into the tools1
- who would like to get started in processing their data and perform downstream analysis and visualisation of their results.1
- who would like to get started in processing their data using a standardised pipeline and perform downstream analysis and visualisation of their results.1
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Eligibility
- First come first served8
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