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Bioinformatics course timetable

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Tue 21 Jan – Fri 7 Mar

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January 2025

Thu 23
Using the Ensembl Genome Browser (ONLINE LIVE TRAINING) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

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.

Additional information
  • 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. 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.
Fri 24
Ensembl REST API workshop (ONLINE LIVE TRAINING) [Places] 09:30 - 16:30 Bioinformatics Training Facility - Online LIVE Training

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 is aimed at researchers and developers interested in exploring Ensembl beyond the website. The workshop covers how to use the Ensembl REST APIs, including understanding the major endpoints and how to write scripts to call them.


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

Additional information
  • 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. 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.
Tue 28
EMBL-EBI: Network Analysis with Cytoscape (ONLINE LIVE TRAINING) (1 of 2) [Places] 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training

This course introduces the basic theory and concepts of network analysis. Attendees will learn how to construct protein-protein interaction networks and subsequently use these to overlay large-scale data such as that obtained through RNA-Seq or mass-spec proteomics. The course will focus on giving attendees hands-on experience in the use of one of the most used open-source Network Visualisation Platforms, Cytoscape. The course will also access and analyse the data through Cytoscape apps, including IntAct app.


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

Additional information
  • 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. 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.
Wed 29
EMBL-EBI: Network Analysis with Cytoscape (ONLINE LIVE TRAINING) (2 of 2) [Places] 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training

This course introduces the basic theory and concepts of network analysis. Attendees will learn how to construct protein-protein interaction networks and subsequently use these to overlay large-scale data such as that obtained through RNA-Seq or mass-spec proteomics. The course will focus on giving attendees hands-on experience in the use of one of the most used open-source Network Visualisation Platforms, Cytoscape. The course will also access and analyse the data through Cytoscape apps, including IntAct app.


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

Additional information
  • 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. 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.

February 2025

Mon 3
Bulk RNA-seq analysis (ONLINE LIVE TRAINING) (1 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

In this course you will acquire practical skills in RNA-seq data analysis. You will learn about quality control, alignment, and quantification of gene expression against a reference transcriptome. Additionally, you will learn to conduct downstream analysis in R, exploring techniques like PCA and clustering for exploratory analysis. The course also covers differential expression analysis using the DESeq2 R/Bioconductor package. Furthermore, the course covers how to generate visualisations like heatmaps and performing gene set testing to link differential genes with established biological functions or pathways.


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

Additional information
  • 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. 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.
Tue 4
Introduction to the Unix command line (IN-PERSON) [Places] 09:30 - 17:30 Bioinformatics Training Facility - The Pembroke Teaching Rooms

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 and 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.

Additional information
  • 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. 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.
Fri 7
Introduction to R (ONLINE LIVE TRAINING) (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

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.


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

Additional information
  • 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. 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.
Bulk RNA-seq analysis (ONLINE LIVE TRAINING) (2 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

In this course you will acquire practical skills in RNA-seq data analysis. You will learn about quality control, alignment, and quantification of gene expression against a reference transcriptome. Additionally, you will learn to conduct downstream analysis in R, exploring techniques like PCA and clustering for exploratory analysis. The course also covers differential expression analysis using the DESeq2 R/Bioconductor package. Furthermore, the course covers how to generate visualisations like heatmaps and performing gene set testing to link differential genes with established biological functions or pathways.


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

Additional information
  • 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. 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.
Mon 10
Bulk RNA-seq analysis (ONLINE LIVE TRAINING) (3 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

In this course you will acquire practical skills in RNA-seq data analysis. You will learn about quality control, alignment, and quantification of gene expression against a reference transcriptome. Additionally, you will learn to conduct downstream analysis in R, exploring techniques like PCA and clustering for exploratory analysis. The course also covers differential expression analysis using the DESeq2 R/Bioconductor package. Furthermore, the course covers how to generate visualisations like heatmaps and performing gene set testing to link differential genes with established biological functions or pathways.


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

Additional information
  • 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. 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.
Wed 12
Single-cell RNA-seq analysis (ONLINE LIVE TRAINING) (1 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing. This course offers an introduction to single-cell RNA sequencing (scRNA-seq) analysis. Participants will gain hands-on experience with key software packages and methodologies for processing, analyzing, and interpreting scRNA-seq data. Key topics include data preprocessing, quality control, normalization, dimensionality reduction, batch correction and data integration, cell clustering and differential expression and abundance analysis. By the end of the course, students will be equipped with the skills to independently conduct and critically analyse data from scRNA-seq experiments.


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

Additional information
  • 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. 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.
Thu 13
Prompting for biologists: using AI chatbots for effective data analysis (IN-PERSON) new [Places] 09:30 - 13:00 Bioinformatics Training Room, Craik-Marshall Building

As the use of AI chatbots continues to rise, it is crucial to understand what they are, how they work, and how to make the most of them. Prompting is the method of interacting with AI, and as AI chatbots become more openly and widely available, a good and effective prompt could make all the difference.

In this course, we will provide background on the history of AI chatbots as well as an understanding of how they work. We will provide hands-on use cases of how to prompt like a bioinformatician/software engineer as well as providing strategies and tactics of prompting to unleash the full potential of AI chatbots in biological data analysis. This course is aimed at researchers with no computational background.


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

Additional information
  • ♿ 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 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.
Fri 14
Introduction to R (ONLINE LIVE TRAINING) (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

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.


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

Additional information
  • 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. 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.
Mon 17
Working with bacterial genomes (ONLINE LIVE TRAINING) (1 of 4) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This comprehensive course equips you with essential skills and knowledge in bacterial genomics analysis, primarily using Illumina-sequenced samples. You'll gain an understanding of how to select the most appropriate analysis workflow, tailored to the genome diversity of a given bacterial species. Through hands-on training, you'll apply both de novo assembly and reference-based mapping approaches to obtain bacterial genomes for your isolates. You will apply standardised workflows for genome assembly and annotation, including quality assessment criteria to ensure the reliability of your results. Along with typing bacteria using methods such as MLST, you'll learn how to construct phylogenetic trees using whole genome and core genome alignments, enabling you to explore the evolutionary relationships among bacterial isolates. You’ll extend this to estimate a time-scaled phylogeny using a starting phylogenetic tree. Lastly, you'll apply methods to detect antimicrobial resistance genes. As examples we will use Mycobacterium tuberculosis, Staphylococcus aureus and Streptococcus pneumoniae, allowing you to become well-equipped to conduct bacterial genomics analyses on a range of species.


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

Additional information
  • 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. 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.
Wed 19
Single-cell RNA-seq analysis (ONLINE LIVE TRAINING) (2 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing. This course offers an introduction to single-cell RNA sequencing (scRNA-seq) analysis. Participants will gain hands-on experience with key software packages and methodologies for processing, analyzing, and interpreting scRNA-seq data. Key topics include data preprocessing, quality control, normalization, dimensionality reduction, batch correction and data integration, cell clustering and differential expression and abundance analysis. By the end of the course, students will be equipped with the skills to independently conduct and critically analyse data from scRNA-seq experiments.


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

Additional information
  • 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. 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.
Fri 21
Working with bacterial genomes (ONLINE LIVE TRAINING) (2 of 4) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This comprehensive course equips you with essential skills and knowledge in bacterial genomics analysis, primarily using Illumina-sequenced samples. You'll gain an understanding of how to select the most appropriate analysis workflow, tailored to the genome diversity of a given bacterial species. Through hands-on training, you'll apply both de novo assembly and reference-based mapping approaches to obtain bacterial genomes for your isolates. You will apply standardised workflows for genome assembly and annotation, including quality assessment criteria to ensure the reliability of your results. Along with typing bacteria using methods such as MLST, you'll learn how to construct phylogenetic trees using whole genome and core genome alignments, enabling you to explore the evolutionary relationships among bacterial isolates. You’ll extend this to estimate a time-scaled phylogeny using a starting phylogenetic tree. Lastly, you'll apply methods to detect antimicrobial resistance genes. As examples we will use Mycobacterium tuberculosis, Staphylococcus aureus and Streptococcus pneumoniae, allowing you to become well-equipped to conduct bacterial genomics analyses on a range of species.


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

Additional information
  • 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. 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.
Mon 24
Working with bacterial genomes (ONLINE LIVE TRAINING) (3 of 4) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This comprehensive course equips you with essential skills and knowledge in bacterial genomics analysis, primarily using Illumina-sequenced samples. You'll gain an understanding of how to select the most appropriate analysis workflow, tailored to the genome diversity of a given bacterial species. Through hands-on training, you'll apply both de novo assembly and reference-based mapping approaches to obtain bacterial genomes for your isolates. You will apply standardised workflows for genome assembly and annotation, including quality assessment criteria to ensure the reliability of your results. Along with typing bacteria using methods such as MLST, you'll learn how to construct phylogenetic trees using whole genome and core genome alignments, enabling you to explore the evolutionary relationships among bacterial isolates. You’ll extend this to estimate a time-scaled phylogeny using a starting phylogenetic tree. Lastly, you'll apply methods to detect antimicrobial resistance genes. As examples we will use Mycobacterium tuberculosis, Staphylococcus aureus and Streptococcus pneumoniae, allowing you to become well-equipped to conduct bacterial genomics analyses on a range of species.


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

Additional information
  • 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. 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.
Tue 25
Generalised linear models (IN-PERSON) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building

Generalised linear models are the kind of models we would use if we had to deal with non-continuous response variables. For example, this happens if you have count data or a binary outcome.

This course aims to introduce generalised linear models, using the R software environment. Similar to Core statistics using R this course addresses the practical aspects of using these models, so you can explore real-life issues in the biological sciences. The Generalised linear models course builds heavily on the knowledge gained in the core statistics sessions, which means that the Core statistics using R course is a firm prerequisite for joining.

There are several aims to this course:

1. Be able to distinguish between linear models and generalised linear models

2. Analyse binary outcome and count data using R

3. Critically assess model fit

R is an open-source programming language so all of the software we will use in the course is free. We will be using the R Studio interface throughout the course. Most of the code will be focussed around the tidyverse and tidymodels packages, so a basic understanding of the tidyverse syntax is essential.


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

Additional information
  • ♿ 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. 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.
Wed 26
Single-cell RNA-seq analysis (ONLINE LIVE TRAINING) (3 of 3) [Full] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing. This course offers an introduction to single-cell RNA sequencing (scRNA-seq) analysis. Participants will gain hands-on experience with key software packages and methodologies for processing, analyzing, and interpreting scRNA-seq data. Key topics include data preprocessing, quality control, normalization, dimensionality reduction, batch correction and data integration, cell clustering and differential expression and abundance analysis. By the end of the course, students will be equipped with the skills to independently conduct and critically analyse data from scRNA-seq experiments.


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

Additional information
  • 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. 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.
Fri 28
Working with bacterial genomes (ONLINE LIVE TRAINING) (4 of 4) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

This comprehensive course equips you with essential skills and knowledge in bacterial genomics analysis, primarily using Illumina-sequenced samples. You'll gain an understanding of how to select the most appropriate analysis workflow, tailored to the genome diversity of a given bacterial species. Through hands-on training, you'll apply both de novo assembly and reference-based mapping approaches to obtain bacterial genomes for your isolates. You will apply standardised workflows for genome assembly and annotation, including quality assessment criteria to ensure the reliability of your results. Along with typing bacteria using methods such as MLST, you'll learn how to construct phylogenetic trees using whole genome and core genome alignments, enabling you to explore the evolutionary relationships among bacterial isolates. You’ll extend this to estimate a time-scaled phylogeny using a starting phylogenetic tree. Lastly, you'll apply methods to detect antimicrobial resistance genes. As examples we will use Mycobacterium tuberculosis, Staphylococcus aureus and Streptococcus pneumoniae, allowing you to become well-equipped to conduct bacterial genomics analyses on a range of species.


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

Additional information
  • 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. 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.

March 2025

Mon 3
Protein structure modelling (IN-PERSON) new (1 of 4) [Full] 09:30 - 13:00 Bioinformatics Training Room, Craik-Marshall Building

Note: This course currently has no available spaces, as we're using this page to get audience interest in the course. Please register on the waiting list or register your interest to be notified when spaces become available or when new sessions are added. Your registration ensures you'll be the first to know.


Determining the 3 dimensional (3D) structure of a protein from its amino sequence is vital for understanding its core biological functions. This can be done using experimental approaches, which are the standard for validating high-resolution and accurate structures. However, these methods can be costly, time-consuming and technically difficult to achieve for certain proteins. To complement these approaches, computational methods can be used, which increase the speed of prediction, can be scaled to higher throughput and are much cheaper to run.

This course covers how to computationally predict the 3D structure of proteins from their amino acid sequences. We will focus on AlphaFold, a software that has revolutionised this process due to its outstanding (near-experimental) prediction accuracy. Other key aspects will be covered such as retrieving structural information from public databases, evaluating the quality of the predicted models, model visualisation with PyMOL, multimer predictions, prediction of ligand binding sites and docking. After this course you should be able to produce 3D predictions of your proteins, while critically evaluating the output of the methods covered in the course.


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

Additional information
  • ♿ 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. 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.
Tue 4
Protein structure modelling (IN-PERSON) new (2 of 4) [Full] 09:30 - 13:00 Bioinformatics Training Room, Craik-Marshall Building

Note: This course currently has no available spaces, as we're using this page to get audience interest in the course. Please register on the waiting list or register your interest to be notified when spaces become available or when new sessions are added. Your registration ensures you'll be the first to know.


Determining the 3 dimensional (3D) structure of a protein from its amino sequence is vital for understanding its core biological functions. This can be done using experimental approaches, which are the standard for validating high-resolution and accurate structures. However, these methods can be costly, time-consuming and technically difficult to achieve for certain proteins. To complement these approaches, computational methods can be used, which increase the speed of prediction, can be scaled to higher throughput and are much cheaper to run.

This course covers how to computationally predict the 3D structure of proteins from their amino acid sequences. We will focus on AlphaFold, a software that has revolutionised this process due to its outstanding (near-experimental) prediction accuracy. Other key aspects will be covered such as retrieving structural information from public databases, evaluating the quality of the predicted models, model visualisation with PyMOL, multimer predictions, prediction of ligand binding sites and docking. After this course you should be able to produce 3D predictions of your proteins, while critically evaluating the output of the methods covered in the course.


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

Additional information
  • ♿ 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. 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.
Wed 5
Protein structure modelling (IN-PERSON) new (3 of 4) [Full] 09:30 - 13:00 Bioinformatics Training Room, Craik-Marshall Building

Note: This course currently has no available spaces, as we're using this page to get audience interest in the course. Please register on the waiting list or register your interest to be notified when spaces become available or when new sessions are added. Your registration ensures you'll be the first to know.


Determining the 3 dimensional (3D) structure of a protein from its amino sequence is vital for understanding its core biological functions. This can be done using experimental approaches, which are the standard for validating high-resolution and accurate structures. However, these methods can be costly, time-consuming and technically difficult to achieve for certain proteins. To complement these approaches, computational methods can be used, which increase the speed of prediction, can be scaled to higher throughput and are much cheaper to run.

This course covers how to computationally predict the 3D structure of proteins from their amino acid sequences. We will focus on AlphaFold, a software that has revolutionised this process due to its outstanding (near-experimental) prediction accuracy. Other key aspects will be covered such as retrieving structural information from public databases, evaluating the quality of the predicted models, model visualisation with PyMOL, multimer predictions, prediction of ligand binding sites and docking. After this course you should be able to produce 3D predictions of your proteins, while critically evaluating the output of the methods covered in the course.


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

Additional information
  • ♿ 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. 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.
Extracting biological information from gene lists (ONLINE LIVE TRAINING) [Full] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training

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.


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

Additional information
  • 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. 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.
Thu 6
Protein structure modelling (IN-PERSON) new (4 of 4) [Full] 09:30 - 13:00 Bioinformatics Training Room, Craik-Marshall Building

Note: This course currently has no available spaces, as we're using this page to get audience interest in the course. Please register on the waiting list or register your interest to be notified when spaces become available or when new sessions are added. Your registration ensures you'll be the first to know.


Determining the 3 dimensional (3D) structure of a protein from its amino sequence is vital for understanding its core biological functions. This can be done using experimental approaches, which are the standard for validating high-resolution and accurate structures. However, these methods can be costly, time-consuming and technically difficult to achieve for certain proteins. To complement these approaches, computational methods can be used, which increase the speed of prediction, can be scaled to higher throughput and are much cheaper to run.

This course covers how to computationally predict the 3D structure of proteins from their amino acid sequences. We will focus on AlphaFold, a software that has revolutionised this process due to its outstanding (near-experimental) prediction accuracy. Other key aspects will be covered such as retrieving structural information from public databases, evaluating the quality of the predicted models, model visualisation with PyMOL, multimer predictions, prediction of ligand binding sites and docking. After this course you should be able to produce 3D predictions of your proteins, while critically evaluating the output of the methods covered in the course.


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

Additional information
  • ♿ 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. 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.
Fri 7
Linear mixed effects models (IN-PERSON) (1 of 2) [Full] 09:30 - 17:00 Bioinformatics Training Facility - The Pembroke Teaching Rooms

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.

Additional information
  • 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. 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.