Abstract Detail

Education and Outreach

Eaton, Deren [1].

Teaching phylogenetics and evolution with interactive Python coding exercises.

Learning to read and understand phylogenetic trees (tree-thinking) is fundamental to understanding evolution, and is often introduced at the beginning of introductory botany, zoology, or biodiversity courses. Phylogenetic inference provide a basis for most modern systematics, and these inference methods/software are often students' first introduction to bioinformatics and computational research. As computational skills have become fundamental to biological research, and to the modern workforce, it is increasingly important that computational literacy be introduced at early stages of education, and be pervasive throughout. Towards this goal, I have developed a series of online interactive coding exercises (notebooks) intended for teaching phylogenetics and evolution in Python. Instructors and students can run the exercises for free in any web browser without need to install any software. These notebooks are designed for both introductory level lessons (e.g., tree-thinking, plotting trees, parsimony tree inference), and advanced levels (e.g., maximum-likelihood inference, ancestral state reconstructions, population genetics). Exercises introduce simple and generic coding skills alongside biological lessons teaching domain specific knowlege. Here I share some examples based on recent Python libraries developed in my lab, including toytree, ipcoal, and shadie.

1 - Columbia University, Ecology, Evolution, And Environmental Biology, 1200 Amsterdam Ave. , Schermerhorn Ext. Office 1007, New York, NY, 10027, United States

life history
self-directed learning.

Presentation Type: Poster
Number: PEO003
Abstract ID:489
Candidate for Awards:None

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