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  1. Getting Started with R: An Introduction for Biologists

    Collections | 08 Mar 2019 | Posted by David Leaf

    https://qubeshub.org/community/members/2971/collections/r

  2. The New Statistics with R: An Introduction for Biologist

    Collections | 08 Mar 2019 | Posted by David Leaf

    https://qubeshub.org/community/members/2971/collections/r

  3. 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

    https://qubeshub.org/publications/1002/?v=1

  4. Joya Mukerji

    https://qubeshub.org/community/members/10206

  5. Working with plant phenology data and fitting a nonlinear model using least squares in R

    21 Dec 2018 | Teaching Materials | Contributor(s):

    By Madeleine Bonsma-Fisher1, Ahmed Hasan1

    University of Toronto

    A participatory live-coding lesson on working with NEON phenology data and fitting a sine-wave model todetermine when different species get and lose their leaves.

    https://qubeshub.org/publications/978/?v=1

  6. Kate S Boersma

    https://qubeshub.org/community/members/10172

  7. Caitlin Hicks Pries

    https://qubeshub.org/community/members/10140

  8. Geraldine Klarenberg

    Name tag: https://www.name-coach.com/geraldine-klarenberg

    https://qubeshub.org/community/members/9762

  9. Introduction to R Course

    05 Nov 2018 | Teaching Materials

    Free Introduction to R Course at DataCamp

    https://qubeshub.org/publications/914/?v=1

  10. DataCamp

    05 Nov 2018 | Teaching Materials

    DataCamp: The Easiest Way to Learn Data Science Online

    https://qubeshub.org/publications/913/?v=1

  11. 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.

    https://qubeshub.org/publications/907/?v=1

  12. BIO103R: Bio 103 and 104 Labs in R at URI

    29 Oct 2018 | Teaching Materials | Contributor(s):

    By Rachel Schwartz1, Linda Forrester1

    University of Rhode Island

    GitHub repository for Bio 103 and 104 Labs in R at University of Rhode Island

    https://qubeshub.org/publications/886/?v=1

  13. BIO 263 Ecological Data Analysis

    29 Oct 2018 | Teaching Materials | Contributor(s):

    By Rachel Schwartz1, Linda Forrester1

    University of Rhode Island

    Course materials for BIO 263 Ecological Data Analysis

    https://qubeshub.org/publications/885/?v=1

  14. BIO 439/539: Big Data Analysis

    29 Oct 2018 | Teaching Materials | Contributor(s):

    By Rachel Schwartz1, Linda Forrester1

    University of Rhode Island

    Course materials for BIO 439/539: Big Data Analysis

    https://qubeshub.org/publications/884/?v=1

  15. 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

    https://qubeshub.org/publications/883/?v=1

  16. Data Analysis for the Life Sciences

    23 Oct 2018 | Teaching Materials | Contributor(s):

    By Rafael A Irizarry1, Michael I Love1

    Harvard University

    An online stats book written completely in R

    https://qubeshub.org/publications/841/?v=1

  17. R Reference Card

    23 Oct 2018 | Teaching Materials | Contributor(s):

    By Tom Short

    EPRI PEAC

    Summary of reference info for using R

    https://qubeshub.org/publications/840/?v=1

  18. Rstudio cheatsheets

    22 Oct 2018 | Teaching Materials

    Cheatsheets are quickstart guides to using some of the most popular packages and features of Rstudio.

    https://qubeshub.org/publications/839/?v=1

  19. 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.

    https://qubeshub.org/publications/838/?v=1

  20. Ecology and Epidemiology in R

    22 Oct 2018 | Teaching Materials | Contributor(s):

    By Paul Esker

    Kansas State University

    Ecology and epidemiology in R: Modeling dispersal gradients.

    https://qubeshub.org/publications/837/?v=1

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