COURSE UNIT TITLE

: PYTHON AND LINUX FOR BIOINFORMATICS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BST 5006 PYTHON AND LINUX FOR BIOINFORMATICS ELECTIVE 3 0 0 12

Offered By

Biomedicine and Health Technologies

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR GÖKHAN KARAKÜLAH

Offered to

Biomedicine and Health Technologies

Course Objective

This course aims to to provide students with basics of Linux environment, and scripting and programming skills for biological data analysis.

Learning Outcomes of the Course Unit

1   To be able to work with Linux command line
2   To be able to develop Bash scripts
3   To be able to use Python programming language for biological data analysis
4   To be able to access programmatically public databases to extract useful information with Python programming language
5   To be able to develop analysis pipelines for biological data analysis with Bash or Python

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Linux and the operating system
2 Basic commands and bash scripting
3 Text editors, shells, bash, and the command line
4 Python strings, text, numbers, dates, and times
5 Iterators, generators, files, I/O
6 Functions
7 Modules and Packages
8 Sequence objects and I/O
9 MIDTERM
10 Multiple sequence alignment and BLAST
11 Accessing public databases with BioPython
12 Pathway analysis
13 Sequence motif analysis
14 Cluster analysis
15 Supervised learning methods
16 Assignment Presentations

Recomended or Required Reading

Textbook(s): 1. Biopython Tutorial and Cookbook, Jeff Chang, Brad Chapman, Iddo Friedberg, Thomas Hamelryck, Michiel de Hoon, Peter Cock, Tiago Antao, Eric Talevich, Bartek Wilczy ski
2. Beazley, David, and Brian K. Jones. Python cookbook. " O'Reilly Media, Inc.", 2013.

Planned Learning Activities and Teaching Methods

Oral presentation, literature search and discussion

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 MTE MIDTERM EXAM
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE ASG * 0.30 + MTE * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.30 + MTE * 0.30 + RST * 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

gokhan.karakulah@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 8 112
Preparation for midterm exam 1 15 15
Preparation for final exam 1 20 20
Preparing assignments 1 50 50
Preparing presentations 1 30 30
Project Preparation 1 15 15
Final 1 10 10
Midterm 1 5 5
TOTAL WORKLOAD (hours) 299

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8
LO.1555
LO.255
LO.355
LO.45555
LO.5555