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Bioinformatics Training

Bioinformatics course timetable

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Tue 18 May – Thu 29 Jul

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June 2021

Tue 1
Introduction to R for Biologists (ONLINE LIVE TRAINING) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors to assist you with instant and personalised feedback and to help you to run/execute the scripts which we will be using during the course. 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.

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.

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.

Wed 2
Introduction to R for Biologists (ONLINE LIVE TRAINING) (2 of 2) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors to assist you with instant and personalised feedback and to help you to run/execute the scripts which we will be using during the course. 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.

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.

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.

Mon 7
Complex Network Analysis for Biologists (ONLINE LIVE TRAINING) new Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors to assist you with instant and personalised feedback and to help you to run/execute the scripts which we will be using during the course. 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.

Complex natural systems permeate many aspects of everyday life—including human intelligence, social media, biomedicine, agriculture, economics, even our personal and professional relationships. The past decade has seen intensification of research into structural and dynamical properties of complex networks. This course will introduce the basic principles of network theory, and hands-on DIY Network analysis using Cytoscape, one of the most widely used global platforms for construction and analysis of biomolecular networks such as gene regulatory interactions, protein complexes, hydrogen-bonding meshwork in active sites and neuronal networks. The aim is to conceptualize your own textual, tabular or genomic datasets as networks, and to understand how simple topological features can help to decipher complex properties of systems and processes.

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.

Tue 8
Next Generation Sequencing Platforms and Bioinformatics Analysis (ONLINE LIVE TRAINING) (1 of 2) Finished 09:00 - 12:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online. 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.

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.

Wed 9
Next Generation Sequencing Platforms and Bioinformatics Analysis (ONLINE LIVE TRAINING) (2 of 2) Finished 09:00 - 12:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online. 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.

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.

Thu 10
An Introduction to Solving Biological Problems with Python (ONLINE LIVE TRAINING) (1 of 2) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

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 course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core concepts of Python including Python syntax, data structures and reading/writing files. These are illustrated by a series of example programs. Upon completion of the course, participants will be able to write simple Python programs.

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.

Fri 11
An Introduction to Solving Biological Problems with Python (ONLINE LIVE TRAINING) (2 of 2) Finished 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

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 course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core concepts of Python including Python syntax, data structures and reading/writing files. These are illustrated by a series of example programs. Upon completion of the course, participants will be able to write simple Python programs.

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.

Wed 30
Analysis of bulk RNA-seq data (ONLINE LIVE TRAINING) (1 of 3) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

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.

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.

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.

July 2021

Thu 1
Analysis of bulk RNA-seq data (ONLINE LIVE TRAINING) (2 of 3) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

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.

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.

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.

Fri 2
Analysis of bulk RNA-seq data (ONLINE LIVE TRAINING) (3 of 3) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

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.

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.

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.

Mon 5
Introduction to working with UNIX and bash (ONLINE LIVE TRAINING) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

PLEASE NOTE that until further notice, due to the evolving situation with Coronavirus no courses will be offered as classroom based at the Training Facility. The Bioinformatics Team will be teaching the course live online in conjunction with the presenters.

Using the Linux operating system and the bash command line interface, we will demonstrate the basic structure of the UNIX operating system and how we can interact with it using a basic set of commands. Applying this, we will learn how to navigate the filesystem, manipulate text-based data and structure simple pipelines out of these commands.

Building on the techniques learnt so far, we will then construct bash scripts combining the commands and structures already learnt into more complex, reusable tools. We will look at how we can apply these scripts to common problems faced in UNIX environments such as: communicating with remote servers; managing custom software installations and integrating these tools into our simple pipelines.

This course is targeted at participants with no prior experience working with UNIX-like systems (OSX, Linux) or command line interfaces.

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.

Tue 6
High Performance Computing: An Introduction (ONLINE LIVE TRAINING) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

PLEASE NOTE that until further notice, due to the evolving situation with Coronavirus no courses will be offered as classroom based at the Training Facility. The Bioinformatics Team will be teaching the course live online in conjunction with the presenters.

Have you heard about High Performance Computing, but are not sure what it is or whether it is relevant for your work? Would you like to use a HPC, but are not sure where to start? Are you using your personal computer to run computationally demanding tasks, which take long and slow down your work? Do you need to use software that runs on Linux, but don't have access to a Linux computer? If any of these questions apply to you, then this course might be for you!

Knowing how to work on a High Performance Computing system is an essential skill for applications such as bioinformatics, big-data analysis, image processing, machine learning, parallelising tasks, and other high-throughput applications.

In this course we will cover the basics of High Performance Computing, what it is and how you can use it in practice. This is a hands-on workshop, which should be accessible to researchers from a range of backgrounds and offering several opportunities to practice the skills we learn along the way.

As an optional session for those interested, we will also introduce the (free) HPC facilities available at Cambridge University (the course is not otherwise Cambridge-specific).

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.

Mon 12
An Introduction to MATLAB for biologists (ONLINE LIVE TRAINING) (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

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 course aims to give you an introduction to the basics of Matlab. During the two day course we will use a practical based approach to give you the confidence to start using Matlab in your own work. In particular we will show you how to write your own scripts and functions and how to use pre-written functions. We will also explore the many ways in which help is available to Matlab users. In addition we will cover basic computer programming in Matlab to enable you to write more efficient scripts.

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.

Tue 13
An Introduction to MATLAB for biologists (ONLINE LIVE TRAINING) (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

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 course aims to give you an introduction to the basics of Matlab. During the two day course we will use a practical based approach to give you the confidence to start using Matlab in your own work. In particular we will show you how to write your own scripts and functions and how to use pre-written functions. We will also explore the many ways in which help is available to Matlab users. In addition we will cover basic computer programming in Matlab to enable you to write more efficient scripts.

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.

Wed 14
An Introduction to Machine Learning (ONLINE LIVE TRAINING) (1 of 3) [Places] 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

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.

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.

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.

Thu 15
An Introduction to Machine Learning (ONLINE LIVE TRAINING) (2 of 3) [Places] 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

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.

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.

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.

Fri 16
An Introduction to Machine Learning (ONLINE LIVE TRAINING) (3 of 3) [Places] 09:30 - 17:00 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

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.

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.

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.

Wed 28
Introduction to R for Biologists (ONLINE LIVE TRAINING) (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors to assist you with instant and personalised feedback and to help you to run/execute the scripts which we will be using during the course. 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.

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.

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.

Thu 29
Introduction to R for Biologists (ONLINE LIVE TRAINING) (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

PLEASE NOTE The Bioinformatics Team are presently teaching as many courses live online, with tutors to assist you with instant and personalised feedback and to help you to run/execute the scripts which we will be using during the course. 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.

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.

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.