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R for Molecular Biosciences: Home

The guide was created to support the course, R for Molecular Biosciences, an introductory undergraduate course in data science.

Introduction

This guide is a resource for students enrolled in BCHM 495, R for Molecular Biosciences.  However, this guide may be useful to anyone that has an interest in analyzing molecular or genomics data with R.

Course Philosophy

People learn by doing.  You cannot learn to program or analyze data by passively watching others.  You cannot learn to use tools such as R and RStudio without making mistakes.  You will not make mistakes unless you try to do something new.  We will make many mistakes in this class, but, ultimately, you will acquire new skills and knowledge along the way.

  I hope that in this year to come, you make mistakes.  Because if you are making mistakes, then you are making new things, trying new things, learning, living, pushing yourself, changing yourself, changing your world. You're doing things you've never done before, and more importantly, you're Doing Something...

Neil Gaiman, 2011, http://journal.neilgaiman.com/2011/12/my-new-year-wish.html

Learning to program is challenging, especially if you have limited experience.  The intent of this class is to provide you a basic introduction to data analysis and programming with R with an emphasis on data generated by research in the molecular biosciences.  Do not expect to be an expert in 16 weeks, but this course should put you on the path for future learning opportunities.

Bioinformatics in the News

Current news stories in Bioinformatics

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Librarians

 
 
Pete E. Pascuzzi
Assistant Professor, Libraries
Assistant Professor of Biochemistry (by courtesy)
Associate Member, Purdue Center for Cancer Research
Office: Wilmeth Active Learning Center, Room 3053A
765.494.3620
ppascuzz@purdue.edu