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The Unix shell (command line) is a powerful and essential tool for modern researchers, in particular those working in computational disciplines such as bioinformatics and large-scale data analysis. In this course we will explore the basic structure of the Unix operating system and how we can interact with it using a basic set of commands. You will learn how to navigate the filesystem, manipulate text-based data and combine multiple commands to quickly extract information from large data files. You will also learn how to write scripts, use programmatic techniques to automate task repetition.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.
• Guidance on visiting Cambridge and finding accommodation is available here.

This event introduces participants to the KNIME Analytics Platform, an open source data science platform with a visual workflow editor, that can be used by users without prior programming experience or integrated with existing scripts written in R or Python.

These sessions are aimed towards anyone who has an interest in building data science workflows with different kinds of life science data. The sessions will cover how to aggregate data from different sources (e.g., files, databases, web services), how to calculate simple statistics (e.g., for data exploration), network mining (e.g., protein-protein interactions) and big data analytics (e.g., next-generation sequencing data).

The webinar will combine practical and taught content to demonstrate how users can use KNIME to design and utilise reproducible data science workflows, such as analytics tasks, and better explore and understand their data.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

This course gives an introduction to linear mixed effects models, also called multi-level models or hierarchical models, for the purposes of using them in your own research or studies.

We emphasise the practical skills and key concepts needed to work with these models, using applied examples and real datasets.

After completing the course, you should have:

• A conceptual understanding of what mixed effects models are, and when they should be used
• Familiarity with fitting and interpreting mixed effects models using the lme4 package in R

Please note that this course builds on knowledge of linear modelling, therefore should not be considered a general introduction to statistical modelling.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.
• Guidance on visiting Cambridge and finding accommodation is available here.

How much data would you lose if your laptop was stolen? Have you ever emailed your colleague a file named 'final_final_versionEDITED'? Have you ever struggled to import your spreadsheets into R? Would you be able to write a Data Management Plan as part of a grant proposal?

As a researcher, you will encounter research data in many forms, ranging from measurements, numbers and images to documents and publications. Whether you create, receive or collect data, you will certainly need to organise it at some stage of your project. This workshop will provide an overview of some basic principles on how we can work with data more effectively. We will discuss the best practices for research data management and organisation so that our research is auditable and reproducible by ourselves, and others, in the future.

Course materials are available here

This event is part of a series of training courses organized in collaboration with the Bioinformatics Core Facility at CRUK Cambridge Institute.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Join us for a two-hour workshop on image processing and analysis in MATLAB. This practical session provides a series of example workflows to extract quantitative data from image files.

This workshop is the first event in Imaging ONE WORLD, a series of events bringing together scientists working from home to deliver workshops and talks on imaging theory and analysis. An initiative made up of scientists, imaging systems and software providers in collaboration to deliver high quality training to the image analysis community.

Although not a necessity, we recommend attending the Introduction to MATLAB course run at the Training Facility and / or the Intro to MATLAB using MathWorks prior to the workshop. For the MathsWorks course you will need to sign up for a MathWorks Account. All University of Cambridge members should be eligible to obtain a MathWorks Account. Create an account using your institution email address.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

Mouse Genome Informatics (MGI) is the international database resource for the laboratory mouse and provides integrated genetic, genomic, and biological data to facilitate the study of human health and disease.

MGI is a free, highly curated resource and offers web and programmatic access to a complete catalogue of mouse genes and genome features, functional annotations, a comprehensive catalogue of mutant and knockout alleles, phenotype and human disease model annotations, gene expression, variation and sequence data.

This workshop will be composed of ~20min overview and ~1 hour hands-on, interactive tutorial.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

This module introduces a deeper exploration of bioinformatics analysis of genomic data, providing a greater understanding of the different approaches to mapping and alignment of genome sequence data, programming and scripting, along with approaches for the detection and analysis of genomic changes, gene expression and network analysis.

This two day course will cover network-based approaches to visualise and analyse complex biological ‘big’ data and model pathway systems. The course will be centred on the use of BioLayout Express3D, a tool developed between scientists at the University of Edinburgh and EBI over the last 10 years.

BioLayout provides rapid and versatile means to explore and integrate very large datasets, providing a stunning interface to visualise the relationships between 10’s of thousands of data points. Originally designed for the analysis of microarray data, it is equally effective in analysing data matrices from other analysis platforms.

Day one of the course will introduce principles of network analysis and their use as a generic medium to understand relationships between entities. We will introduce the basics of network visualisation and navigation within BioLayout and principles of correlation analysis of data matrices. We will then explore how data can be explored and clustered within the tool and how you can use the software to rapidly extract meaning from large and complex datasets.

Day two will focus on pathway modelling. We will explain how to collate information about a given system of interest from the literature, and to turn this information into a logic-based pathway model. We will then explore how these models can be parametrised and imported into BioLayout where simulations can be run that model the dynamics of these systems under different conditions. For more information see: http://www.virtuallyimmune.org/

A draft agenda can be found here.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

This course provides an introduction to next generation sequencing (NGS) data analysis methodologies. Lectures will give insight into how biological knowledge can be generated from RNA-seq, ChIP-seq and DNA-seq experiments and illustrate different ways of analyzing such data. Practicals will consist of computer exercises that will enable the participants to apply statistical methods to the analysis of RNA-seq, ChIP-seq and DNA-seq data under the guidance of the lecturers and teaching assistants. It is aimed at researchers who are applying or planning to apply NGS technologies and bioinformatics methods in their research.

The timetable for this event can be found here.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

Day 1 will introduce you to next generation sequencing technologies (NGS) and how they work, providers, common bioinformatics workflows, standardised file types, quality control. This session will include an introduction to Galaxy. Galaxy is an open, web-based platform for data-intensive life science research that enables non-bioinformaticians to create, run, tune, and share their own bioinformatic analyses.

Day 2 will be hands-on practicals on using Galaxy to explore sequencing quality control, before and after removal of low quality samples. This forms the core of all NGS analyses and this day will conclude with how this data pipes into gene expression studies, variant calling and genome assemblies.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

• Nowomics - Access to the latest data and papers relevant to your research
• Nowomics is a new website to help biologists stay up to date with the latest data and papers relevant to their research. Try it here.
• Nowomics tracks new papers and many types of data in online repositories. You ‘follow’ the genes and processes you work on to see a Twitter-like news feed of new papers, annotation, interactions, curated comments and more.
• For each gene you can also include information from orthologues and related genes directly in your news feed.
• Data are currently included for human, mouse, rat, fly and plant.
• This short workshop will show you how to use the Beta version of Nowomics to find the latest information for genes & keywords, how to set up your personalised news feed and configure email alerts. We’ll also demonstrate new portals to help researchers working on Drosophila or Arabidopsis find the latest and most popular papers.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Ontologies have long provided a core foundation in the organization of biomedical entities, their attributes, and their relationships. With over 500 biomedical ontologies currently available there are a number of new and exciting opportunities emerging in using ontologies for large scale data sharing and data analysis.

This tutorial will help you understand what ontologies are and how they are being used in computational biology and bioinformatics. It will include hands-on examples and exercises and an introduction to Onto2Vec and OPA2Vec, two methods that can be used to learn semantic similarity measures in a data- and application-driven way.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Open Targets is a public-private partnership to use human genetics, genomic data and drug information for systematic identification and prioritisation of therapeutic targets. This module introduces the Open Targets partnership, its underlying projects and the bioinformatics resources for researchers studying associations of human genes with diseases.

In this 90 minute long webinar, Denise Carvalho-Silva, will focus on Open Targets Platform and Open Targets Genetics, open source tools of integrated genetic, genomic and chemical data for target-disease associations.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

This is a first course on machine learning. It aims to provide a foundation for future work with machine learning. This course will get you to the point where you can confidently engage with literature referencing machine learning, but it is not designed to get you to the point where you can actively use modern machine learning methods in your own research. It will however signpost for you which of our other courses will be relevant if you want to get to that stage.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.

This course is aimed to provide the tools to create machine learning models in R using the CARET Library. This is a pre-requisite for the intermediate and advanced courses on supervised and unsupervised learning courses.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.
• Guidance on visiting Cambridge and finding accommodation is available here.

Jalview hands-on training course is for anyone who works with sequence data and multiple sequence alignments from proteins, RNA and DNA.

Jalview is free software for protein and nucleic acid sequence alignment generation, visualisation and analysis. It includes sophisticated editing options and provides a range of analysis tools to investigate the structure and function of macromolecules through a multiple window interface. For example, Jalview supports 8 popular methods for multiple sequence alignment, prediction of protein secondary structure by JPred and disorder prediction by four methods. Jalview also has options to generate phylogenetic trees, and assess consensus and conservation across sequence families. Sequences, alignments and additional annotation can be accessed directly from public databases and journal-quality figures generated for publication.

The course involves of a mixture of talks and hands-on exercises.

Day 1 is an introduction to protein multiple sequence alignment editing and analysis with Jalview.

Day 2 focuses on using Jalview for RNA sequence analysis, and also integrating cDNA and protein analysis and covers more advanced applications after lunch.

Day 3 concentrates on protein secondary structure prediction with JPred version 4 as well as protein sub-family analysis to identify functionally important residues.

There will be opportunities for attendees to get advice on analysis of their own sequence families.

Further information, including some training videos, is also available.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

This course covers data resources and analytical approaches for the discovery and interpretation of biomacromolecular structures.

Day 1 focuses on public repositories of structural data (Protein Data Bank and Electron Microscopy Data Bank) and resources for protein analysis and classification (Pfam, InterPro and HMMER).

Day 2 covers how to find information about the structure and function of your protein sequence using CATH, principles of modern state-of-the-art protein modelling with Phyre2 and methods for predicting the effects of mutations on protein structure and function using the SAAP family of tools.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

This course covers analytical approaches for the interpretation of biomacromolecular structures including how to find information about the structure and function of your protein sequence using CATH, principles of modern state-of-the-art protein modelling with Phyre2 and methods for predicting the effects of mutations on protein structure and function using the SAAP family of tools. In addition, we will look at mapping genetic variants onto structures as well as visualisation and basic analysis of protein structures.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

This course covers the potential pitfalls of short-read sequencing studies and provides options for visualisation and quality control (QC) for early detection and diagnosis of issues. You will gain an understanding of Illumina sequencing and different QC metrics that can be extracted from sequencing reads, such as base quality scores. The course also covers how QC metrics vary across different library types and thus distinguish between expected and unexpected QC results. You will be introduced to key software tools including FastQC, FastQ Screen, and MultiQC to carry out quality assessment of your sequencing data.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.

This course introduces concepts about reproducibility that can be used when you are programming in R. We will explore how to create notebooks - a way to integrate your R analyses into reports using Rmarkdown. The course also introduces the concept of version control. We will learn how to create a repository on GitHub and how to work together on the same project collaboratively without creating conflicting versions of files.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.
• Guidance on visiting Cambridge and finding accommodation is available here.

The course will teach intermediate R object-oriented programming and how to build a fully functional R package.

Relevant teaching materials are available here and the sequences example package used as template in the course can be found here.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

High-throughput data analyses usually involve many data processing steps, including the use of a range of command line tools and scripts to transform, filter, aggregate and visualise data. Each tool may require a specific set of inputs and options to be defined and, as we chain multiple tools together, this can become challenging to manage. As analyses pipelines become more complex and with the ever-increasing amounts of data being collected in research, reproducible and scalable automatic workflow management becomes increasingly important.

The Snakemake workflow management system is a tool to create reproducible and scalable data analyses pipelines/workflows. Workflows are described via a human-readable, Python-based language. They can be seamlessly scaled to server, cluster, grid and cloud environments, without the need to modify the workflow definition. Finally, Snakemake workflows can entail a description of the required software, which will be automatically deployed to any execution environment.

With over 500k downloads on Bioconda, and over 2k citations, Snakemake is a widely used and accepted standard for reproducible data science that has powered numerous research goals and publications.

This 1-day workshop will cover the principles for building workflows using Snakemake, as well as more advanced strategies to fully customise, automate and scale your analysis.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

This course is aimed at researchers who want to learn core skills and best practices for scientific computing. It will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

The course covers the core skills needed to be productive in a small research team:

• Unix command line (and how to automate repetitive tasks);
• Python or R (and how to grow a program in a modular, testable way); and
• version control with Git (and how to track and share work efficiently).

Further information is available here.

Applicants for this course are requested to complete a pre-course survey. This will be used to tailor the course content to the audience research interests and background.

This event is organized in collaboration with Software Carpentry.

This optional extra day builds on what we learned in the main event on 15-19 April.

During the day we will have additional trainers available to help you implementing the skills and concepts that you have learned during the previous week. We encourage participants to send a brief explanation of their research to us before the session, together with a snippet of their data. This way we can prepare additional resources, where applicable.

To ensure sufficient support on the day, we encourage participants to register for this additional session before the start of the main event. However, if you are unsure at the moment and decide you would like to join during the week itself then this is of course possible too!

If you do not have a University of Cambridge Raven account please book or register your interest here.

Statistics are an important part of most modern studies and being able to effectively use a statistical package will help you to understand your results.

This course provides an introduction to some statistical techniques through the use of the R language. Topics covered include: Chi2 and Fisher tests, descriptive statistics, t-test, analysis of variance and regression.

Students will run analyses using statistical and graphical skills taught during the session.

The course manual can be found here.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.