COURSE UNIT TITLE

: COMPUTATIONAL GENOMICS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BST 6009 COMPUTATIONAL GENOMICS ELECTIVE 3 0 0 12

Offered By

Biomedicine and Health Technologies

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR GÖKHAN KARAKÜLAH

Offered to

Biomedicine and Health Technologies

Course Objective

To gain a thorough understanding of the bioinformatics methods and tools for retrieving, manipulating, analyzing and interpreting genomic data.

Learning Outcomes of the Course Unit

1   Familiarity with state-of-the art computational methods
2   Conduct of in silico experimental research
3   Efficient similarity searches on sequence databases
4   Identification of nucleotide and amino acid sequence patterns
5   Inference of gene and protein function by applying in silico techniques
6   Usage of computational methods for protein structure analysis and prediction
7   Elucidation of protein interactions by using bioinformatics approaches
8   In silico dissection of microRNAs
9   Application of bioinformatics tools for the analysis of transcriptional and post-transcriptional gene regulation
10   Presentation of research findings

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Similarity Searches on Sequence Databases-I
2 Similarity Searches on Sequence Databases-II
3 Detection of Gene and Protein Sequence Motifs-I
4 Detection of Gene and Protein Sequence Motifs-II
5 Phylogenetic Analysis
6 Analysis of Protein Structure and Function-I
7 Analysis of Protein Structure and Function-II
8 Midterm
9 Secondary and Tertiary Protein Structure Prediction-I
10 Secondary and Tertiary Protein Structure Prediction-II
11 Protein Interaction Informatics
12 MicroRNA informatics
13 Bioinformatics analysis of gene regulation-I
14 Bioinformatics analysis of gene regulation-II
15 Assignment Presentations
16 Final Exam

Recomended or Required Reading

Bioinformatics and Functional Genomics, by Jonathan Pevsner October. Wiley-Blackwell, 2015
ISBN: 978-1-118-58178-0

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


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 10 140
Preparation for midterm exam 1 20 20
Preparation for final exam 1 30 30
Preparing assignments 1 40 40
Preparing presentations 1 30 30
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 308

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8
LO.1555
LO.255
LO.355
LO.455
LO.555
LO.655
LO.755
LO.8
LO.9
LO.105