SDS 348, Spring 2020

This is the home page for class SDS 348, Computational Biology and Bioinformatics. All relevant course materials will be posted here.

Syllabus: SDS348_syllabus_spring2020.pdf

Revised syllabus due to COVID-19: SDS348_syllabus_spring2020_revised.pdf

Lectures

1. Jan 21, 2020 – Introduction, R Markdown

2. Jan 23, 2020 – R review

3. Jan 28, 2020 – Data visualization with ggplot2

4. Jan 30, 2020 – Data visualization with ggplot2

5. Feb 4, 2020 – Working with tidy data

6. Feb 6, 2020 – Working with tidy data

7. Feb 11, 2020 – Working with tidy data

8. Feb 13, 2020 – Rearranging data tables with tidyr

9. Feb 18, 2020 – Principal Components Analysis (PCA)

10. Feb 20, 2020 – k-means clustering

11. Feb 25, 2020 – Binary prediction/logistic regression

12. Feb 27, 2020 – Sensitivity/Specificity, ROC curves

13. Mar 3, 2020 – Training and test data sets, cross-validation

14. Mar 5, 2020 – Introduction to python, basic data structures

15. Mar 10, 2020 – Control flow in python

16. Mar 12, 2020 – Functions in python

17. Mar 31, 2020 – More on python data structures, classes

18. Apr 2, 2020 – Working with files

19. Apr 7, 2019 – Introduction to Biopython

20. Apr 9, 2020 – Working with gene features and genomes

21. Apr 14, 2019 – Running queries on Entrez

22. Apr 16, 2020 – Regular expressions

23. Apr. 21, 2020 – Using regular expressions to analyze data

24. Apr. 23, 2020 – Using regular expressions to analyze data

25. Apr. 28, 2020 – Aligning sequences

26. Apr. 20, 2020 – Global and local alignments, BLAST

27. May 5, 2020 – Multiple sequence alignments and phylogenetic trees

28. May 7, 2020 – Plotting geospatial data

Homeworks

All homeworks are due by noon (12:00pm) on the day they are due. Homeworks need to be submitted as pdf files on Canvas.

Labs

1. Jan 22, 2020

2. Jan 29, 2020

3. Feb 4, 2020

4. Feb 11, 2020

5. Feb. 18, 2020

6. Feb. 25, 2020

7. Mar. 3, 2020

8. Mar. 11, 2020

9. Apr. 1, 2020

10. Apr. 8, 2020

11. Apr. 15, 2020

12. Apr. 22, 2020

Projects

All projects are due by noon (12:00pm) on the day they are due. Projects need to be submitted on Canvas, both in pdf format and as source code (plus data where needed).