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- University of Cambridge Bioinformatics Training147
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Keyword
- HDRUK147
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Scientific topic
- Data rendering
- Bioinformatics365
- Data visualisation147
- Data mining110
- 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
- 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 courses147
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Country
- United Kingdom147
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Target audience
- Graduate students115
- Postdocs and Staff members from the University of Cambridge115
- Institutions and other external Institutions or individuals114
- Everyone is welcome to attend the courses10
- please review the policies.10
- 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 aimed at biologists interested in microbiology7
- The course is aimed primarily at mid-career scientists – especially those whose formal education likely included statistics6
- but who have not perhaps put this into practice since.6
- <span style="color:#FF0000">After you have booked a place5
- 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
- but not essential as we will walk through a MS typical experiment and data as part of learning about the tools.5
- if you are unable to attend any of the live sessions and would like to work in your own time5
- including for registered university students.<span style="color:#FF0000">5
- please email the Team as Attendance will be taken on all courses. A charge is applied for non-attendance5
- Anyone who is using sequencing as part of their work and/or research.4
- Familiarity with mass spectrometry or proteomics in general is desirable4
- Researchers who are applying or planning to apply image analysis in their research4
- Researchers who want to extract quantitative information from microscopy images4
- 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.4
- This course is aimed at researchers with an interest in metabolomics and its applications4
- prokaryotic genomics and antimicrobial resistance.4
- Institutions and other external institutions or individuals.3
- No prior experience in the analysis of these types of data is required.3
- Postdocs and other Research Staff from the University of Cambridge3
- The course is open to Graduate students3
- This course is aimed at researchers with an interest in metabolomics and its applications.3
- analysis of complex microbiomes and antimicrobial resistance.3
- prokaryotic genomics3
- <span style="color:#0000FF"> Non-members of the University of Cambridge to pay £575 </span style>2
- <span style="color:#0000FF">All Members of the University of Cambridge to pay £250 </span style> <span style="color:#FF0000">A booking will only be approved and confirmed once the fee has been paid in full.</span style>2
- <span style="color:#FF0000">There is no fee charged for this event''<span style="color:#FF0000">2
- This course is aimed at researchers with no prior experience in the analysis of ChIP-seq data2
- pathways and diseases.2
- <span style="color:#FF0000">Please note that all participants attending this course will be charged a registration fee.1
- <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
- <span style="color:#FF0000">There is no fee charged for this event''<span style="color:#FF0000">.1
- 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
- Applicants are expected to have an interest in learning about bioinformatics and/or are in the beginning stages of using bioinformatics in their research with the need to develop their skills and knowledge further.1
- BioImage Analysts with some experience of basic microscopy image analysis1
- Biophysicists1
- Cell Biologists1
- Day1 is intended for biologists and computer scientists interested in using LithoGraphX. Some experience in imaging is desirable but not required.1
- Day2 is intended for computer scientists wanting either to write their own algorithm or automate complex protocols. Basic python knowledge and familiar with C++ are required.1
- Institutions and other external Institutions or individuals.1
- No previous knowledge of programming is required for this course.1
- 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 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 aimed at individuals working across biological and biomedical sciences who have little or no experience in bioinformatics.1
- This course is aimed at individuals working across biological and biomedical sciences who have little to no experience in bioinformatics.1
- 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 is suitable for all users who have an interest in biomedical research and therapeutics. A special emphasis will be given on drug discovery and target validation. It will also be useful to those who seek for practical examples on how large-scale genomic experiments and computational techniques are integrated and visualised in a web platform.1
- This course is suitable for anyone who has an interest in biomedical and therapeutic research with a special emphasis on target identification and prioritisation1
- This course is suitable for anyone who has an interest in biomedical research and therapeutics with a special emphasis on drug discovery and target validation. It is also useful to those who wish to find out how large-scale genomic experiments1
- This course may be of interest to physical scientists looking to develop their knowledge of Python coding in the context of bioimage analysis1
- This hands-on event is suitable for anyone who has an interest in building data science workflows with different kinds of life science data.1
- This webinar is suitable for students and early career researchers in the Life Sciences.1
- cellular models of disease and computational techniques are used to identify and validate the causal links between targets1
- computational and statistical techniques are used to identify and validate the causal links between targets1
- early stages of drug discovery. It is also useful to those who wish to find out how large-scale genomic experiments1
- 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 served11
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