Useful Resources

Here we have curated a list of resources related to biomedical data science that might be helpful in your career.

Is your favourite resource missing from our list? Let us know at integrate@imm.ox.ac.uk

 

 

Resource list:

General

 

  

Team Research/ Research Culture

 

 

 

  • Teams Build Dreams (University of Manchester) have a collection of case studies around team-science and also provide training to teams embarking on collaborative research projects
  • Valuing Voices (University of York) have developed a comprehensive tool to guide researchers at all career stages through the 5 principles of equitable and responsible research, complete with signposting to complementary resources
  • Liston Lab Careers Resources - a number of resources for various academic career stages covering topics from grant-writing, to balancing science and family, to nurturing positive research cultures.
  

Responsible, Reproducible and Reusable Research

 

 

 

 

  

Single Cell Analysis

 

 

 

 

 

  • Single-cell best practices (mostly python; Fabian Theis et al) Best practices of single-cell sequencing analysis. This book will teach you the most common analysis steps ranging from pre-processing to visualization to statistical evaluation and beyond
  • Orchestrating Single-Cell Analysis book aka OSCA (Lun et al) teaches users some common workflows for the analysis of single-cell RNA-seq data (scRNA-seq). This book will show you how to make use of cutting-edge Bioconductor tools to process, analyze, visualize, and explore scRNA-seq data.
  • Single cell RNA-seq data analysis with R (2019) (tutorial; several videos) This lecture series was recorded during the ELIXIR EXCELERATE course "Single cell RNA-seq data analysis with R" (27.-29.5.2019)
  

Statistics

 

 

 

 

 

  • 3blue1brown Mathematics with a distinct visual perspective. Linear algebra, calculus, neural networks, topology, and more.
  • Explained Visually Explained Visually (EV) is an experiment in making hard ideas intuitive inspired the work of Bret Victor's Explorable Explanations. PCA, regression, probability, etc.
  • The Markov-chain Monte Carlo Interactive Gallery Interactive Markov-chain Monte Carlo Javascript demos
  • Modern Statistics for Modern Biology Book by Susan Holmes and Wolfgang Huber. A far-reaching course in practical advanced statistics for biologists using R/Bioconductor, data exploration, and simulation.
  

Communities