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A Quick Guide to Teaching R Programming to Computational Biology Students
22 Oct 2018 | Teaching Materials | Contributor(s):
By Stephen Elgen
University of Cambridge
An introduction from an experienced educator in teaching R to computational biology graduate students.
A Very Basic Tutorial for Performing Linear Mixed Effects Analyses: Tutorial 2
20 Oct 2018 | Teaching Materials | Contributor(s):
By Bodo Winter
University of California, Merced
The second of two tutorials that introduce you to linear and linear mixed models. This tutorial serves as a quick boot camp to jump-start your own analyses with linear mixed effects models.
An evolution curriculum designed around understanding the rise and spread of drug-resistant pathogens
07 Jun 2018 | Teaching Materials | Contributor(s):
By Aditi Pai1, Amanda Gibson2
1. Spelman College 2. Emory University
Poster on teaching concepts in evolution and data science skills in an upper level Biology elective at Spelman College presented at the 2018 QUBES/BioQUEST Summer Workshop
An introduction to population matrix models: a swirl lesson
15 Jun 2020 | Teaching Materials | Contributor(s):
By Jennifer Apple
Students will learn how to set up a population matrix model in R and use it for demographic analysis of a population, including projecting population growth, determining lambda and the stable age...
An Introduction to the R Programming Environment
04 Jan 2019 | Teaching Materials | Contributor(s):
By K. A. Garrett1, P. D. Esker1, A. H. Sparks1
Kansas State University
An online module introducing students and biologists to R, published in American Phytopathological Society
BIO 181G: The information age
29 Oct 2018 | Teaching Materials | Contributor(s):
By Rachel Schwartz1, Linda Forrester1
University of Rhode Island
Course materials for BIO181G: The information age
BIO 263 Ecological Data Analysis
Course materials for BIO 263 Ecological Data Analysis
BIO 439/539: Big Data Analysis
Course materials for BIO 439/539: Big Data Analysis
BIO103R: Bio 103 and 104 Labs in R at URI
GitHub repository for Bio 103 and 104 Labs in R at University of Rhode Island
Cleaning Data with R and the Tidyverse in Swirl
09 Jun 2020 | Teaching Materials | Contributor(s):
By Rachel Hartnett
Oklahoma State University
The overall goal is to help students learn common data cleaning procedures on a dataset once they’ve collected measurements and before they are able to start their analysis. This swirl lesson is...
Coding Club: A Positive Peer-Learning Community
22 Apr 2020 | Teaching Materials | Contributor(s):
By Gergana Daskalova1, Sandra Angers-Blondin1, John Godlee1, Izzy Rich1, Beverly Tan1, Declan Valters1, Haydn Thomas1, Pedro Miranda1, Gabriela Hajduk1, Kat Keogan1, Isla Myers-Smith1, Kyle Dexter1, Christina Coakley1
University of Edinburgh
Free and self-paced tutorials and courses for learning to code out of the University of Edinburgh
Computational Biology using R
30 Oct 2018 | Teaching Materials | Contributor(s):
By Hong Qin
University of Tennessee Chattanooga
This is an introductory level course on computational biology.
Cookbook for R
11 Sep 2018 | Teaching Materials | Contributor(s):
By Winston Chang
The goal of the cookbook is to provide solutions to common tasks and problems in analyzing data.
Data Analysis for the Life Sciences
23 Oct 2018 | Teaching Materials | Contributor(s):
By Rafael A Irizarry1, Michael I Love1
An online stats book written completely in R
05 Nov 2018 | Teaching Materials
DataCamp: The Easiest Way to Learn Data Science Online
Ecology and Epidemiology in R
By Paul Esker
Ecology and epidemiology in R: Modeling dispersal gradients.
Introduction to R Course
Free Introduction to R Course at DataCamp
IPMpack: an R package for Integral Projection Models
By C. Jessica E. Metcalf1, Sean M. McMahon2, Roberto Salguero-Gómez3, Eelke Jongejans4, Cory Merow5
1. University of Oxford 2. Smithsonian Tropical Research Institute 3. University of Queensland 4. Radbound University Nijmegen 5. STRI and University of Connecticut
IPMpack is an R package (R Development Core Team 2013) that allows users to build and analyse Integral Projection Models.
Linear Models and Linear Mixed Effects in R: Tutorial 1
The first of two tutorials that introduce you to linear and linear mixed models.
NEON Data in the Classroom: Quantifying Spatial Patterns
23 Jul 2020 | Teaching Materials | Contributor(s):
By Kusum Naithani
University of Arkansas, Fayetteville, AR 72701
Students build on fundamental concepts of spatial patterns and combine this knowledge with the open-data from the National Ecological Observatory Network to quantify spatial autocorrelation and...