- Home
- Events
Filters
Sort
-
-
Filter Clear filters
-
-
Start
- -
-
-
-
Content provider
- University of Cambridge Bioinformatics Training102
- Show N_FILTERS more
-
-
-
Keyword
- HDRUK
- ABR11
- Bioinformatics7
- Data analysis3
- R-programming2
- Data Visualization2
- Data exploration2
- Data visualisation2
- User experience2
- Visual analytics2
- data visualization2
- ComputationalBiology1
- Cross domain (cross-domain)1
- Cytoscape1
- Data carpentry1
- Data handling1
- Data presentation1
- Datavisualisation1
- Ecology1
- Experimental design1
- Git1
- Introduction to bioinformatics1
- Life science1
- Metabolomics1
- Multiomics1
- Multiomics data integration1
- Plotting data1
- Proteomics1
- Python1
- R1
- R Studio1
- RStudio1
- Research presentation1
- Scientific communication1
- Scientific presentation1
- Shell1
- SoftwareCarpentry1
- Systems biology, Pathway analysis, Network analysis, Microarray data analysis, Nanomaterials1
- VLSCI1
- Version control1
- Visualization1
- bioinformatics1
- computer-science1
- lifescience1
- machine learning1
- mySQL1
- networks and pathways1
- transcriptomics1
- Show N_FILTERS more
-
-
-
Scientific topic
- Data rendering
- Bioinformatics284
- Data visualisation102
- Aerobiology78
- Behavioural biology78
- Biological rhythms78
- Biological science78
- Biology78
- Chronobiology78
- Cryobiology78
- Reproductive biology78
- Data mining75
- Pattern recognition75
- Functional genomics34
- Comparative transcriptomics31
- Transcriptome31
- Transcriptomics31
- Active learning19
- Ensembl learning19
- Kernel methods19
- Knowledge representation19
- Machine learning19
- Neural networks19
- Recommender system19
- Reinforcement learning19
- Supervised learning19
- Unsupervised learning19
- Bioimaging14
- Biological imaging14
- Coding RNA12
- EST12
- Exomes12
- Exons12
- Fusion genes12
- Fusion transcripts12
- Gene features12
- Gene structure12
- Gene transcript features12
- Gene transcripts12
- Genome annotation12
- Genomes12
- Genomics12
- Introns12
- Personal genomics12
- PolyA signal12
- PolyA site12
- Signal peptide coding sequence12
- Synthetic genomics12
- Transit peptide coding sequence12
- Viral genomics12
- Whole genomes12
- cDNA12
- mRNA12
- mRNA features12
- ChIP-exo10
- ChIP-seq10
- ChIP-sequencing10
- Chip Seq10
- Chip sequencing10
- Chip-sequencing10
- Python10
- Python program10
- Python script10
- py10
- DNA methylation8
- Epigenetics8
- Histone modification8
- Methylation profiles8
- Epigenomics7
- Phylogenetics5
- Codon usage4
- DNA chips4
- DNA microarrays4
- Data management4
- Exometabolomics4
- Expression4
- Gene expression4
- Gene expression profiling4
- Gene transcription4
- Gene translation4
- Genotype4
- Genotype and phenotype4
- Genotype and phenotype resources4
- Genotype-phenotype4
- Genotype-phenotype analysis4
- Genotyping4
- LC-MS-based metabolomics4
- MS-based metabolomics4
- MS-based targeted metabolomics4
- MS-based untargeted metabolomics4
- Mass spectrometry-based metabolomics4
- Metabolites4
- Metabolome4
- Metabolomics4
- Metabonomics4
- Metadata management4
- NMR-based metabolomics4
- Phenotype4
- Phenotyping4
- Protein structure4
- Show N_FILTERS more
-
-
-
Event type
- Workshops and courses102
- Show N_FILTERS more
-
-
-
Country
- United Kingdom102
- Show N_FILTERS more
-
-
-
Target audience
- Postdocs and Staff members from the University of Cambridge102
- Institutions and other external Institutions or individuals101
- Graduate students99
- 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 primarily at mid-career scientists – especially those whose formal education likely included statistics6
- but who have not perhaps put this into practice since.6
- Researchers who are applying or planning to apply image analysis in their research4
- Researchers who want to extract quantitative information from microscopy images4
- This course is aimed at researchers with an interest in metabolomics and its applications4
- The course is open to Graduate students3
- <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
- 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 aimed at biologists interested in microbiology1
- 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
- analysis of complex microbiomes and antimicrobial resistance.1
- but not essential as we will walk through a MS typical experiment and data as part of learning about the tools.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
- prokaryotic genomics1
- seeking an introductory course into the tools1
- Show N_FILTERS more
-
-
-
Eligibility
- First come first served11
- Show N_FILTERS more
-
- Only show online events
- Hide past events
- Show disabled events