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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS IEE 5750 COMPUTATIONAL BIOLOGY ELECTIVE 3 0 0 8

Offered By

Bioengineering (English)

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR HASAN HAVITÇIOĞLU

Offered to

Bioengineering (English)

Course Objective

This course will begin with a broad description of cellular organization in a molecular biology perspective including nucleic acid and protein structure. Computational methods for pattern detection and clustering will be introduced in the analysis of amino acid sequences of proteins. Probabilistic models of genetic evolution will be developed along with sequence alignment and motif detection algorithms. RNA and DNA analysis with microarrays will be discussed.

Learning Outcomes of the Course Unit

1   To get algorithmic, mathematical, statistical, and computational methods that are central in bioinformatics and computational biology. 2   To have knowledge about the development and testing of effective computer programs in bioinformatics 3   To get information about the development and optimization of biological databases. Hücrenin çevresiyle etkileşim ve iletişimin mekanizmalarını kavramak 4   To be capable of getting important biological results that are obtained from the use of these methods, programs, and databases 5   To have information on ethical issues

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 What is Computational Biology 2 Molecular Biology: an Information Science 3 Molecular Biology Information - DNA Molecular Biology Information: Protein Sequence 4 Molecular Biology Information: Macromolecular Structure 5 Molecular Biology Information: Protein Structure Details 6 PPT Slide 7 Molecular Biology Information: Whole Genomes 8 Gene Expression Datasets: the Transcriptosome 9 Array Data 10 Other Whole-Genome Experiments Molecular Biology Information: Other Integrative Data

Recomended or Required Reading

To be announced.

Planned Learning Activities and Teaching Methods

Assessment Methods

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

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 15 8 120 Final 1 15 15 Midterm 1 15 15 Quiz etc. 6 8 48 TOTAL WORKLOAD (hours) 198

Contribution of Learning Outcomes to Programme Outcomes

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