skip to navigation skip to content
- Select training provider - (Cambridge Admissions Office)
Instructor-led course

Provided by: Bioinformatics


This course is not scheduled to run.


[ Show past events ]



Register interest
Register your interest - if you would be interested in additional dates being scheduled.


Events available

Winter School - Bioinformatics Data Exploration for Biologists: An introduction to Data Exploration, Statistics and Reproducibility (Online)
Special£


Description

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.

Target audience
  • This course is aimed at individuals working across biological and biomedical sciences who have little or no experience in bioinformatics.
  • Applicants are expected to have an interest in learning about bioinformatics and/or are in the beginning stages of using bioinformatics in their research with the need to develop their skills and knowledge further.
  • No previous knowledge of programming is required for this course.
  • The course is open to Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
  • Further details regarding eligibility criteria are available here

Please note that ALL participants attending this course will be charged a registration fee.

  • Non-members of the University of Cambridge to pay £575
  • All Members of the University of Cambridge to pay £250

A booking will only be approved and confirmed once the fee has been paid in full.

Prerequisites
  • Biological/Biomedical background knowledge
  • No previous knowledge of programming/coding is required for this course.
Topics covered

Bioinformatics, Data visualisation, Data handling, R, Statistics, Reproducibility

Objectives

As a result of attending the course, participants should be able to:

  • Define opportunities and challenges of using bioinformatics in research
  • Format, query, visualise, and explore datasets in R
  • Evaluate which statistical tests are appropriate for a dataset
  • Implement reproducible methods for their research
Aims

The aim of this course is to:

  • Encourage the development of the bioinformatics skills needed to process biological data effectively
  • Provide practical experience with, and guidance on, how to manage and analyse examples of biological data
  • Introduce best practices with regards to working with data reproducibly
Format

Presentations, demonstrations, and practicals

Timetable
Registration fees
  • All participants attending this course will be charged a registration fee.
  • Non-members of the University of Cambridge to pay 575.00 GBP
  • All Members of the University of Cambridge to pay 250.00 GBP.
  • A booking will only be approved and confirmed once the fee has been paid in full.
  • Further details regarding the charging policy are available here
Duration

5

Theme
Bioinformatics

Events available