COURSE UNIT TITLE

: BIOINFORMATICS ALGORITHMS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CSE 5005 BIOINFORMATICS ALGORITHMS ELECTIVE 3 0 0 9

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ZERRIN IŞIK

Offered to

Industrial Ph.D. Program In Advanced Biomedical Technologies
Industrial Ph.D. Program In Advanced Biomedical Technologies
Computer Engineering (Non-Thesis-Evening) (English)
Computer Engineering Non-Thesis (English)
Biomedical Tehnologies (English)
Computer Engineering (English)
Computer Engineering (English)
COMPUTER ENGINEERING (ENGLISH)

Course Objective

The purpose of this course is to enable students to identify solutions for data processing problems in the area of Bioinformatics.

Learning Outcomes of the Course Unit

1   Define data types and data structures for different types biological data
2   Identify probabilistic and statistical methods for processing of biological data
3   Identify supervised and unsupervised learning methods for biological data analysis
4   Solve data processing problems for clinical needs related to Bioinformatics analysis
5   Apply various data analysis methods in real problems in Bioinformatics

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, Biology Review (DNA, RNA, Protein, Cell Components)
2 Introduction to Sequence Alignment Problem
3 Global and Local Alignment with Dynamic Programming
4 Multiple Sequence Alignment
5 Phylogenetic Tree Reconstruction
6 Protein Bioinformatics
7 MIDTERM
8 Raw of Microarray Data Analysis
9 Functional Annotation of Gene Expressions
10 Biological Network and Pathway Analysis
11 Applications of Clustering Algorithms
12 Supervised Learning for Subtype Classification
13 Supervised Learning for Survival Time Prediction
14 Supervised Learning for Biomarker Prediction
15 Student Presentations

Recomended or Required Reading

Textbook(s): Understanding Bioinformatics, M.J. Zvelebil, J.O. Baum, CRC Press, 2007
Supplementary Book: An Introduction to Bioinformatics Algorithms, N.C. Jones, P.A. Pevzner, MIT Press, 2004

Planned Learning Activities and Teaching Methods

Lectures
Literature Research
Assignment
Presentation of Term Project

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 RPR RESEARCH PRESENTATION
4 PAR PARTICIPATION
5 FCG FINAL COURSE GRADE MTE* 0.20 + ASG * 0.20 + RPR * 0.50 + PAR * 0.10


Further Notes About Assessment Methods

None

Assessment Criteria

Assessment will be made based on the success level of assignments, midterm exam and the presentation for the term project.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Assoc.Prof.Dr. Zerrin IŞIK
Dokuz Eylul University
Department of Computer Engineering
Tinaztepe Campus 35160 BUCA/IZMIR
Tel: +90 (232) 3017413
e-mail: zerrin@cs.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 2 28
Preparation for midterm exam 1 20 20
Preparing assignments 3 20 60
Preparing presentations 1 50 50
Other activities within the scope of the atelier pratices 4 6 24
Midterm 1 3 3
TOTAL WORKLOAD (hours) 227

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.144
LO.2443
LO.3443
LO.44554433333
LO.54554434

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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