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Cambridge Academy of Therapeutic Sciences


The following Bioinformatics Training events, taking place at the University of Cambridge, are currently open for booking. Although some of them are already fully booked, we encourage registering as you will be added to the waiting list and notified when a place becomes available.

  • Please note that these courses are only free for University of Cambridge studentsAll other participants will be charged a registration fee in some form.
  • It is the participant’s responsibility to acquire approval from their line manager/supervisor to attend any of these courses.
  • Please review full charging policy at the end of this email.


  • These courses are aimed primarily at mid-career scientists – especially those whose formal education likely included statistics, but who have not perhaps put this into practice since.
  • Graduate students, Postdocs and Staff members from the University of CambridgeAffiliated Institutions and other external Institutions or individuals are eligible to attend
  • Further details regarding eligibility criteria are available here


All scheduled courses can be found at:


February 2021

Mon 22  - Tues 23

Introduction to R for Biologists

9:30 - 17:30 Bioinformatics Training Room, ONLINE

R is one of the leading programming languages in Data Science. It is widely used to perform statistics, machine learning, visualisations and data analyses. It is an open source programming language so all the software we will use in the course is free. This course is an introduction to R designed for participants with no programming experience. We will start from scratch by introducing how to start programming in R and progress our way and learn how to read and write to files, manipulate data and visualise it by creating different plots - all the fundamental tasks you need to get you started analysing your data. During the course we will be working with one of the most popular packages in R; tidyverse that will allow you to manipulate your data effectively and visualise it to a publication level standard.


Thur 25 - Fri 26

EMBL-EBI: Transcriptomics Data and Tools

13:00 - 16:45 Bioinformatics Training Room, ONLINE

This workshop is designed for researchers interested in learning about functional genomics data, how to access, retrieve and use the data from ArrayExpress and hands-on experience in using Expression Atlas, a resource to find information about gene and protein expression across species and biological conditions such as different tissues, cell types, developmental stages and diseases among others. This will include an overview on how gene expression data is curated and analysed in Expression Atlas and a practical activity to demonstrate how to access and visualise gene expression analysis results. These activities should help you answer questions such as "where is my favourite gene expressed?" or "how does its expression change in a disease?".

This workshop is not going to be a session on how to run your own bioinformatics analysis but to use the tools that have been developed in order to be able to take advantage of others’ work and prepare your work to be reproducible.



March 2021

Mon 1 - Fri 5

Transcriptome Analysis for Non-Model Organisms

09:30 - 17:30 Bioinformatics Training Room, ONLINE

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.


Mon 8 - Wed 10

An Introduction to Machine Learning

09:30 - 17:00 Bioinformatics Training Room, ONLINE

Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment.


Mon 15

Extracting biological information from gene lists

09:30 - 17:30 Bioinformatics Training Room, ONLINE

Many experimental designs end up producing lists of hits, usually based around genes or transcripts. Sometimes these lists are small enough that they can be examined individually, but often it is useful to do a more structured functional analysis to try to automatically determine any interesting biological themes which turn up in the lists.

This course looks at the various software packages, databases and statistical methods which may be of use in performing such an analysis. As well as being a practical guide to performing these types of analysis the course will also look at the types of artefacts and bias which can lead to false conclusions about functionality and will look at the appropriate ways to both run the analysis and present the results for publication.

Course materials are available here.



Mon 22 - Wed 24

Analysis of bulk RNA-seq data

09:30 - 17:30 Bioinformatics Training Room, ONLINE

The aim of this course is to familiarize the participants with the primary analysis of RNA-seq data.

This course starts with a brief introduction to RNA-seq and discusses quality control issues. Next, we will present the alignment step, quantification of expression and differential expression analysis. For downstream analysis we will focus on tools available through the Bioconductor project for manipulating and analysing bulk RNA-seq.



Thu 5

Introduction to Scientific Figure Design

09:30 - 17:30 Bioinformatics Training Room, ONLINE

This course provides a practical guide to producing figures for use in reports and publications.

It is a wide ranging course which looks at how to design figures to clearly and fairly represent your data, the practical aspects of graph creation, the allowable manipulation of bitmap images and compositing and editing of final figures.

The course will use a number of different open source software packages and is illustrated with a number of example figures adapted from common analysis tools.

Further information and access to the course materials is here.



Mon 29 - Tues 30

An Introduction to Solving Biological Problems with Python

09:30 - 17:30 Bioinformatics Training Room, ONLINE

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs and customize more complex code to fit their needs.

Course materials are available here.

Please note that the content of this course has recently been updated. This course now mostly focuses on core concepts including Python syntax, data structures and reading/writing files. Concepts and strategies for working more effectively with Python are now the focus of a new 2-days course, Data Science in Python.



All scheduled courses can be found at:

Full details of our charging policy can be found at:

Please note that it is the participant’s responsibility to acquire approval from their line manager/supervisor to attend any of these courses. All non-attendees (including University of Cambridge students) who fail to cancel more than 24 hours before a course, will be charged irrespectively.


Registration charges (Unless otherwise stated):

  • Free for University of Cambridge students.
  • £ 50/day for all University of Cambridge staff, including postdocs, and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level.
  • It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
  • £ 50/day for all other academic participants from External Institutions and Charitable Organizations. These charges must be paid at registration.
  • £ 100/day for all Industry participants. These charges must be paid at registration.

Full details of our charging policy can be found at: