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Content provider
- University of Cambridge Bioinformatics Training22
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Keyword
- HDRUK22
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Scientific topic
- Active learning
- Bioinformatics365
- Data rendering147
- Data visualisation147
- Data mining110
- Pattern recognition110
- Aerobiology86
- Behavioural biology86
- Biological rhythms86
- Biological science86
- Biology86
- Chronobiology86
- Cryobiology86
- Reproductive biology86
- Functional genomics55
- Comparative transcriptomics50
- Transcriptome50
- Transcriptomics50
- 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
- Exometabolomics9
- Histone modification9
- LC-MS-based metabolomics9
- MS-based metabolomics9
- MS-based targeted metabolomics9
- MS-based untargeted metabolomics9
- Mass spectrometry-based metabolomics9
- Metabolites9
- Metabolome9
- Metabolomics9
- Metabonomics9
- Methylation profiles9
- NMR-based metabolomics9
- 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 courses22
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Country
- United Kingdom22
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Target audience
- Institutions and other external Institutions or individuals22
- Postdocs and Staff members from the University of Cambridge22
- Graduate students20
- 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
- This introductory course is aimed at biologists with little or no experience in machine learning.3
- <span style="color:#FF0000">After you have booked a place2
- Students and researchers from life-sciences or biomedical backgrounds2
- The course is open to Graduate students2
- if you are unable to attend any of the live sessions and would like to work in your own time2
- including for registered university students.<span style="color:#FF0000">2
- or will shortly have2
- please email the Team as Attendance will be taken on all courses. A charge is applied for non-attendance2
- the need to apply the techniques presented during the course to biomedical data.2
- who have2
- <span style="color:#FF0000">Please note that all participants attending this course will be charged a registration fee. <span style="color:#0000FF"> Non-members of the University of Cambridge to pay £350. </span style> <span style="color:#0000FF">All Members of the University of Cambridge to pay £175. </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
- <span style="color:#FF0000">Please note that all participants attending this course will be charged a registration fee. <span style="color:#0000FF"> Non-members of the University of Cambridge to pay £400. </span style> <span style="color:#0000FF">All Members of the University of Cambridge to pay £200. </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
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