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• • Target audience
  • Everyone is welcome to attend the courses33
  • please review the policies.33
  • as well as other departmental training within the University of Cambridge (potentially under a different name) so participants who have attended statistics training elsewhere should check before applying.4
  • Anyone who is using sequencing as part of their work and/or research.2
  • Graduates, postgraduates, and PIs, without any previous command-line experience, who want to learn to use the Linux command-line in order to be able to work with large data files.2
  • It may be particularly useful for those who have attended other Facility Courses and now need to process their data on a Linux server. It will also benefit those who find themselves using their personal computers to run computationally demanding analysis/simulations and would like to learn how to adapt these to run on a HPC.2
  • The course is aimed at biologists interested in microbiology2
  • This course is - in abbreviated form - included as part of several DTP and MPhil programmes2
  • This course is aimed at students and researchers of any background.2
  • This course is included as part of several DTP and MPhil programmes2
  • We assume no prior knowledge of what a HPC is or how to use it.2
  • prokaryotic genomics and antimicrobial resistance.2
  • Academia/ Research Institution1
  • Academics, post-graduate students, and anyone looking to learn this essential bioinformatics skill.1
  • Bioinformaticians and wet-lab biologists who can program1
  • Biologists and bioinformaticians1
  • Familiarity with mass spectrometry or proteomics in general is desirable1
  • Graduates, postgraduates, PIs and anyone who wants to learn how to prepare DNA libraries for short read sequencing.1
  • Graduates, postgraduates, and PIs, who are using, or planning to use, RNA-seq technology in their research and want to learn how to process and analyse RNA-seq data.1
  • Graduates, postgraduates, and PIs, who are using, or planning to use, single cell RNA-seq technology in their research and want to learn how to process and analyse single cell RNA-seq data.1
  • Graduates, postgraduates, and PIs, who are using, or planning to use, the statistical software R to manipulate and analyse NGS and other data in their research. This is an introductory level course: no prior experience of R is necessary before starting the workshop.1
  • Life Science Researchers1
  • Master students1
  • Note that we will not cover specific topics in phylogenomics (whole-genome phylogenies) or bacterial genomics.1
  • PhD Students1
  • Please review the policies.1
  • Post Docs1
  • 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.1
  • This course is aimed at researchers dealing with or planning to perform chemical analysis.1
  • 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).1
  • This course is aimed at researchers working on environmentally relevant samples or complex organic matrices of any kind1
  • This course is for researchers who need to automate data analysis tasks for biological research involving next-generation sequence data, for example RNA-seq analysis, variant calling, CHIP-Seq, bacterial genome assembly, etc.1
  • This course is intended for researchers who need to analyse genomic data in order to call genomic variants. Aside from a basic understanding of molecular biology, attendees must have a working knowledge of how to use the Linux BASH command line; our 1-day 'Linux for bioinformatics' course is a suitable background.1
  • This course is targeted at life scientists who would like to explore how AI chatbots can be used to support their data analysis1
  • This workshop is aimed at researchers and technical workers with a background in biology who want to learn programming. The syllabus has been planned with complete beginners in mind; people with previous programming experience are welcome to attend as a refresher but may find the pace a bit slow. If in doubt, take a look at the detailed session content below.1
  • This workshop is aimed at researchers interested in proteins1
  • and related areas1
  • but not essential as we will walk through a MS typical experiment and data as part of learning about the tools.1
  • including lipids and metabolites.1
  • network analysis1
  • programming and bioinformatics tasks.1
  • protein-protein interactions1
  • reproducible research1
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• • Eligibility
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• • Language
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• • Node
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