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8 matching courses
Courses per page: 10 | 25 | 50 | 100


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.

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 be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes.

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. 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.

InterMine is a freely available open-source data warehouse built specifically for the integration and analysis of complex biological data sets.

InterMine-based data analysis platforms are available for many organisms including mouse, rat, budding yeast, plants (over 87 plant genomes), nematodes, fly, zebrafish, Hymenoptera, Planaria, and more recently human.

Genomic and proteomic data within InterMine databases includes pathways, gene expression, interactions, sequence variants, GWAS, regulatory data and protein expression. InterMine provides sophisticated query and visualisation tools both through a web interface and a powerful web service API, with multiple language bindings including Python and R.

This course will focus on programmatic access to InterMine through the API and InterMine searches will be done using Python and R scripts. The exercises will mainly use the fly, human and mouse databases, but the course is applicable to anyone working with data for which an InterMine database is available (a comprehensive list of InterMine databases is available here.

This event is organised alongside a half day course on Biological data analysis using the InterMine User Interface. More information on this event are available 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.

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.

InterMine is a freely available open-source data warehouse built specifically for the integration and analysis of complex biological data.

InterMine-based data analysis platforms are available for many organisms including mouse, rat, budding yeast, plants (over 87 plant genomes), nematodes, fly, zebrafishHymenoptera, Planaria, and more recently human.

Genomic and proteomic data within InterMine databases includes pathways, gene expression, interactions, sequence variants, GWAS, regulatory data and protein expression. InterMine provides sophisticated query and visualisation tools both through a web interface and a powerful web service API, with multiple language bindings including Python and R.

This course will focus on the InterMine web interface and will introduce participants to all aspects of the user interface, starting with some simple exercises and building up to more complex analysis encompassing several analysis tools and comparative analysis across organisms. The exercises will mainly use the fly, human and mouse databases, but the course is applicable to anyone working with data for which an InterMine database is available (a comprehensive list of InterMine databases is available here.)

This event is organised alongside a half day course on Biological data analysis using the InterMine API. More information on this event is available 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.

Introduction to R for Biologists (ONLINE LIVE TRAINING) Wed 28 Oct 2020   09:30 In progress

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.

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.

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.

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.

Introduction to Statistical Analysis (Online) Thu 5 Nov 2020   09:30 [Full]

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 refresher on the foundations of statistical analysis. The emphasis is on interpreting the results of a statistical test, and being able to determine the correct test to apply.

Practicals are conducted using a series of online apps, and we will not teach a particular statistical analysis package, such as R. For courses that teach R, please see the links under "Related courses" .

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

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

This 1-week course provides an introduction to data exploration of biological data. It provides a learning journey starting with learning about how we can automate processes that can be reproduced to analyse our biological data.

The course will begin with discussing what opportunities and challenges are associated with aspects of bioinformatics analyses. We will address a subset of them in greater detail in the central part of the course and provide time for participants to practise using some of the associated bioinformatics tools.

Focusing on solutions around handling biological data, we will cover programming in R, version control, statistical analyses, and data exploration. The R component of the course will cover from the foundations of programming in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming is required. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course 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 your interest by linking here.