Algorithms, data organization and computer programming for bioinformatics2018/19
Archived edition: this page is kept for reference, and some materials or links may no longer be available.
Course material
- Think python
- Learn Python the Hard Way
- Anaconda distribution
- J. Leskovec, A. Rajaraman, J. Ullman, Mining of massive datasets
Syllabus
The course explains the topics listed in the lecture calendar.
Lectures calendar
| Lecture | Date | Topic | Material |
|---|---|---|---|
| L01 | 08/04/2019 | Introduction to python: simple data types, list, and tuples. | |
| L02 | 09/04/2019 | Introduction to python: string, dictionaries, and operations on data structures. | |
| L03 | 10/04/2019 | Introduction to python: functions, modules, and files. | |
| L04 | 15/04/2019 | Pandas. | |
| L05 | 16/04/2019 | Neurons and feed-forward neural networks. | |
| L06 | 17/04/2019 | Tensorflow. | |
| L07 | 17/06/2019 | Link analysis. | |
| L08 | 18/06/2019 | Hadoop and spark. | |
| L09 | 19/06/2019 | Finding similar items. | |
| L10 | 20/06/2019 | Frequent itemsets. | |
| L11 | 21/06/2019 | Regression. |