BIOL 3872

Sci. Computing for Biol.

Lec 01 selected

Best practices for scientific computing and data handling, theory of visualisation, and scripting, teaching students how to create, store, and manipulate data using the object-oriented programming language R. Examples and projects will be drawn from a wide variety of biological areas, covering typical problems encountered with computer use.

Sections

Lecture, pick one

From the syllabus

From the Fall 2026 syllabus by Diego Ibarra. Open the PDF

Grading

9.1%Lab Report 1Introduction to RStudio and R
9.1%Lab Report 2R basics
9.1%Lab Report 3Basic plotting and data exploration
9.1%Lab Report 4Data manipulation and tidyverse
9.1%Lab Report 5SQL databases and R
9.1%Lab Report 6Flow control and functions
9.1%Lab Report 7Temporal data, strings, and web scraping
9.1%Lab Report 8Mapping and geospatial analysis, part 1
9.1%Lab Report 9Mapping and geospatial analysis, part 2
9.1%Lab Report 10Project management and version control
9.1%Lab Report 11Scientific reports with Rmarkdown and knitr
Discussion board participation2% bonus

Course rules

Late work
Assignments lose 10% of their grade for each day they are late.
Missed work
Contact the TA, copy the instructor, and submit an SDA form unless you have an accommodation plan.
Questions
Post course questions on Brightspace discussion boards; use email only for private matters.
Laptop
A personal laptop is mandatory for working with R and RStudio.
Graduate passing grade
Graduate students need at least 70% (B-) to pass.

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