All Bioinformatics courses

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.

• 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.

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.

Congratulations! You have just created a new programme/script that is likely to be of use to other researchers. Naturally, you want to publish this software, others to use it and you to be cited. How hard can that step be? (SPOILER Alert – it’s harder than you think).

• This course explores the myriad challenges in producing code that works on other researchers’ computers and not just yours.
• We tour various possible software solutions and evaluate their suitability
• We examine the potential solution that is Software Containers (focusing on Docker).

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.

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.

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors available to help you work through the course material on a personal copy of the course environment. We aim to simulate the classroom experience as closely as possible, with opportunities for one-to-one discussion with tutors and a focus on interactivity throughout.

This bootcamp provides an in depth look at statistical analyses using R.

Day 1 aims to introduce R as a tool for statistics and graphics, with the main aim being to become comfortable with the R environment. As well as introducing core R language concepts, this course also provides the basics of using the Tidyverse for data manipulation, and ggplot for plotting. It will focus on entering and manipulating data in R and producing simple graphs.

PLEASE NOTE: If you are already comfortable working in R and using the tidyverse package, you might find that you can skip Friday’s training session. Please review the pre-requisites section below for further information.

Day 2-6 (half days) will focus on the statistical possibilities of R, covering from experimental design to analysis of quantitative and qualitative data. Ample time will be given to participants to practise different type of analysis and interact with the trainers to discuss their statistical problems.

This event is organized in collaboration with the Babraham Institutes's Bioinformatics Group and it is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

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 is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences using the R software package.

In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to multiple linear regression. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

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.

This course aims to provide trainers with guidance and tips for developing and delivering training in image analysis, exploring a range of methods appropriate to different learning styles and examining the requirements for a successful course (both scientific and logistic).

The first part of the course will give participants principles of training theory and best practises for developing and delivering their future training content; the second part will be a hackathon to kick start the development of a common set of training materials in image analysis.

This event is organized in collaboration with the Image Analysis Focused Interest Group and is supported by the Royal Microscopical Society.

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.

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors available to help you work through the course material on a personal copy of the course environment. We aim to simulate the classroom experience as closely as possible, with opportunities for one-to-one discussion with tutors and a focus on interactivity throughout.

RNA-Seq technology has been transformative in our ability to explore gene content and gene expression in all realms of biology, and de novo transcriptome assembly has enabled opportunities to expand transcriptome analysis to non-model organisms.

This course provides an overview of modern applications of transcriptome sequencing and popular tools, and algorithms, for exploring transcript reconstruction and expression analysis in a genome-free manner.

Attendees will perform quality assessment and upstream analysis of both Illumina and long reads single molecule sequencing data; the derived transcriptomes will be compared, annotated and used as reference for quantifying transcript expression, leveraging on Bioconductor tools for differential expression analysis. Additional methods will be explored for characterising the assembled transcriptome and revealing biological findings.

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.

Microscopy experiments have proven to be a powerful means of generating information-rich data for biological applications. From small-scale microscopy experiments to time-lapse movies and high-throughput screens, automatic image analysis is more objective and quantitative and less tedious than visual inspection.

This course will introduce users to the free open-source image analysis program CellProfiler and its companion data exploration program CellProfiler Analyst. We will show how CellProfiler can be used to analyse a variety of types of imaging experiments. We will also briefly discuss the basic principles of supervised machine learning with CellProfiler Analyst in order to score complex and subtle phenotypes.

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.

The Ensembl Project provides an interface and an infrastructure for accessing genomic information, including genes, variants, comparative genomics and gene regulation data, covering over 300 vertebrate species. This workshop offers a comprehensive practical introduction to the use of the Ensembl genome browser as well as essential background information.

This course will focus on the vertebrate genomes in Ensembl, however much of what will be covered is also applicable to the non-vertebrates (plants, bacteria, fungi, metazoa and protists) in Ensembl Genomes.

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.