- Home
- Events
Filters
Sort
-
-
Filter Clear filters
-
-
Start
- -
-
-
-
Keyword
- HDRUK78
- ABR2
- Data management plan2
- data organisation2
- licensing2
- life science standards2
- metadata2
- storage2
- Bioinformatics1
- Data skills1
- Neurobiology1
- Open science1
- QCIF1
- R1
- SoftwareCarpentry1
- bioinformatics1
- data collection1
- data management1
- life sciences1
- ols1
- open access1
- open data1
- open source1
- openlifesci1
- preprints1
- Show N_FILTERS more
-
-
-
Scientific topic
- Biology
- Bioinformatics1156
- Genome annotation369
- Exomes366
- Genomes366
- Genomics366
- Personal genomics366
- Synthetic genomics366
- Viral genomics366
- Whole genomes366
- Biological modelling304
- Biological system modelling304
- Systems biology304
- Systems modelling304
- Biomedical research258
- Clinical medicine258
- Experimental medicine258
- General medicine258
- Internal medicine258
- Medicine258
- Bottom-up proteomics169
- Discovery proteomics169
- MS-based targeted proteomics169
- MS-based untargeted proteomics169
- Metaproteomics169
- Peptide identification169
- Protein and peptide identification169
- Proteomics169
- Quantitative proteomics169
- Targeted proteomics169
- Top-down proteomics169
- Data visualisation135
- Data rendering128
- Exometabolomics95
- LC-MS-based metabolomics95
- MS-based metabolomics95
- MS-based targeted metabolomics95
- MS-based untargeted metabolomics95
- Mass spectrometry-based metabolomics95
- Metabolites95
- Metabolome95
- Metabolomics95
- Metabonomics95
- NMR-based metabolomics95
- Data management94
- Metadata management94
- Aerobiology90
- Behavioural biology90
- Biological rhythms90
- Biological science90
- Chronobiology90
- Cryobiology90
- Reproductive biology90
- Computational pharmacology84
- Immunology84
- Pharmacoinformatics84
- Pharmacology84
- Data mining79
- Pattern recognition79
- Comparative transcriptomics70
- Transcriptome70
- Transcriptomics70
- Cloud computing61
- Computer science61
- HPC61
- High performance computing61
- High-performance computing61
- Functional genomics44
- Biomathematics43
- Computational biology43
- Mathematical biology43
- Theoretical biology43
- Epigenomics42
- Disease41
- Pathology41
- Active learning40
- Ensembl learning40
- Kernel methods40
- Knowledge representation40
- Machine learning40
- Neural networks40
- Recommender system40
- Reinforcement learning40
- Supervised learning40
- Unsupervised learning40
- Metagenomics35
- Shotgun metagenomics35
- RNA-Seq analysis33
- Electrophysiology30
- Physiology30
- Pipelines30
- Software integration30
- Tool integration30
- Tool interoperability30
- Workflows30
- High-throughput sequencing29
- Chromosome walking28
- Clone verification28
- DNA-Seq28
- DNase-Seq28
- Show N_FILTERS more
-
-
-
Organizer
- University of Cambridge78
- Institut Français de Bioinformatique (IFB)2
- Australasian Genomic Technologies Association1
- Australian BioCommons1
- BIB i COEINF (Col·legi d'Enginyeria en Informàtica de Catalunya) en representació d'Enginyers de Catalunya1
- Dutch Techcentre for Life Sciences&the BioSB research school&ELIXIR1
- EMBL Heidelberg1
- Open Life Science1
- Software Carpentry1
- VIB Conferences1
- Show N_FILTERS more
-
-
-
Target audience
- Graduate students78
- Institutions and other external Institutions or individuals78
- Postdocs and Staff members from the University of Cambridge78
- 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
- Biologists3
- health professionals2
- Biomedical researchers2
- bioinformaticians2
- Bioinformaticians and wet-lab biologists1
- Life Science Researchers1
- PhD students1
- 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 tutorial will be at an introductory level1
- The tutorial will be of interest to computational biologists who use1
- This is aimed for life scientists with little or no experience in long-read sequencing that are looking at implementing these approaches in their research.1
- but not essential as we will walk through a MS typical experiment and data as part of learning about the tools.1
- but will also describe current research directions and challenges that will be of broad interest to researchers in computational biology.1
- produce or analyse large structured datasets.1
- research software engineers and research data managers working with ELIXIR-supported tools and resources1
- Show N_FILTERS more
-
- Only show online events
- Hide past events
- Hide disabled events