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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS MBG 6133 BIOINFORMATICS DATA SKILLS ELECTIVE 3 0 0 12

Offered By

Molecular Biology and Genetics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSOCIATE PROFESSOR GÖKHAN KARAKÜLAH

Offered to

Molecular Biology and Genetics Molecular Biology and Genetics Biomedicine and Health Technologies

Course Objective

This course aims to to provide students with 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 R programming language for biological data analysis 4   To be able to access programmatically public databases to extract useful information with R programming language 5   To be able to develop analysis pipelines for biological data analysis with Bash and R

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to bioinformatics 2 Setting up and managing a bioinformatics project 3 Remedial unix shell 4 Working with remote machines 5 Git for researchers 6 Bioinformatics data 7 Unix data tools 8 R language 9 MIDTERM 10 Working with range data 11 Working with sequence data 12 Working with alignment data 13 Bioinformatics shell scripting, writing pipelines, and parallelizing tasks 14 Out-of-memory approaches 15 Discussion 16 Assignment Presentations

Recomended or Required Reading

1. Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools Book by Vince Buffalo

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 * 0.20 + MTE * 0.30 + FIN * 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.20 + MTE * 0.30 + RST * 0.50 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Theoretical knowledge will be evaluated by exam

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

gokhan.karakulah@deu.edu.tr

Office Hours

It will be announced later.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparing assignments 4 20 80 Preparing presentations 1 15 15 Preparation for final exam 1 30 30 Preparation for midterm exam 1 20 20 Preparations before/after weekly lectures 14 8 112 Final 1 3 3 Midterm 1 2 2 TOTAL WORKLOAD (hours) 304

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 LO.1 3 LO.2 3 LO.3 3 LO.4 3 LO.5 3