BDS 311 - Computational Approaches to Biological Data

Course Description

Introduces the fundamentals of data science with specific application to biology. Through a practical, problem-based approach, students will examine the theory and practice underlying widely used computational methods in biology. They will develop mastery in the analysis and visualization of large data sets using Python, with applications to genomics, ecology, and other areas of biology. Students will test hypotheses, infer dataset parameters, and make predictions via broadly applicable data science tools.

Instructor

Timothy Warren
tim.warren AT oregonstate.edu

Course Assistants

Nathaniel Davidson (Head) davidson AT oregonstate.edu

Vini Karumuru karumurv AT oregonstate.edu

Divyansh (Divy) divyans AT oregonstate.edu

Syllabus

Weekly Calendar

Date	Topic	Relevant Reading	Assignment
Week 1 01/09, 01/111	Course Goals and Philosophy Unix Shell Scripts Introduction to Pandas	Jupyter Notebook Unix Shell Python Examples Pandas 10 min Reference Pandas tutorial	HW0 (for students who did not take BDS 310) Due Fri 1/12 HW 1 Due Mon 01/22

Week 2 01/16, 01/18	Analyzing Tabular Data with Pandas Time Series and Visualization		HW 2 Due Mon 01/26

Week 3 01/23, 01/25	Pandas synthesis; Using version control to organize your work	matplotlib tutorial Edward Tufte Data Visualization textbook	HW 3 Due Mon 02/04

Week 4 01/30, 02/01	Version Control; Introduction to Random Processes	Inferential Thinking: Chapter 9, Randomness Inferential Thinking: Chapter 10, Sampling	HW 4 Due Mon 02/11

Week 5 02/06, 02/08	Application of Random processes: Permutation Testing	Inferential Thinking: Chapter 11: Testing Hypotheses Chapter 12: Comparing Two Samples Illustrated permutation test	HW 5 Due Mon 02/19

Week 6 02/13, 02/15	Resampling for hypothesis and estimation - the bootstrap	Chapter 12: Comparing Two Samples Illustrated permutation test Chapter 13: Testing Hypotheses Bootstrap schematic News article on origin of bootstrap	HW 6 Due Mon 02/26

Week 7 02/20, 02/22	Testing and predicting relationships in data: Regression and Correlation In-class quiz - Date TBD		HW 7 Due Mon 03/04

Week 8 02/27, 02/29	Regression; Error-minimization for Model Fitting		HW 8 Due Mon 03/11

Week 9 03/05, 03/07	Introduction to Optimization and Machine Learning		HW 09 Due Tues 03/19

Week 10 03/12, 03/14	Putting it all together

Link to hw04 directions: hw04_directions

Link to github pages website creation instruction: GH_pages

Link to github classroom assignment creation and cloning GH_classroom