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 5071 BIOINFORMATICS ALGORITHMS ELECTIVE 3 0 0 6

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR SÜLEYMAN SEVINÇ

Offered to

COMPUTER ENGINEERING
Computer Engineering Non-Thesis
Computer Engineering Non-Thesis
Computer Engineering

Course Objective

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

Learning Outcomes of the Course Unit

1   Define data types and data structures for Bioinformatics
2   Identify probabilistic and statistical methods for processing of Bioinformatics data
3   Identify learning methods and algorithms for Bioinformatics data
4   Solve data storage and processing problems stemming from research and clinical needs related to 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 Data Types
2 ProbabilisticModelling and Inference
3 Learning Algorithms Basics
4 Finite State Machines & Languages
5 Neural Networks and Learning from Biological Data
6 Clustering Algorithms for Biological Data
7 Midterm Exam & Solutions
8 Probabilistic Graphical Models
9 Motif Finding Algorithms
10 Microarrays and Gene Expression
11 Stochastic Grammars and Linguistics
12 Learning Algorithms Revisited
13 Bioinformatics Based Computing Models
14 Applications and Review

Recomended or Required Reading

Textbook(s):
Neil C. Jones and Pavel A. Pevzner, An Introduction to Bioinformatics Algorithms, The MIT Press, 2004 (ISBN-13: 978-0262101066).

Supplementary Book(s):

Baldi, P., Brunak S, Bioinformatics The Machine Learning (Second Edtn) , MIT Press, 2001,
Ewens WJ, Grant GR, Statistical Methods in Bioinformatics An Introduction, Springer, 2005.

Materials: Lecture Notes,problem sets.

Planned Learning Activities and Teaching Methods

Lectures, homeworks, projects

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 PRJ PROJECT
3 MTE MIDTERM EXAM
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE ASG* 0.15 + PRJ * 0.20 + MTE * 0.30 + FIN * 0.35
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) ASG* 0.15 + PRJ * 0.20 + MTE * 0.30 + RST * 0.35


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)

Prof.Dr. Suleyman Sevinc
Dokuz Eylul University
Department of Computer Engineering
Tinaztepe Campus 35160 BUCA/IZMIR
Tel: +90 (232) 301 74 01
e-mail: suleyman.sevinc@cs.deu.edu.tr

Office Hours

TBA

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 4 56
Preparation for midterm exam 1 10 10
Preparation for final exam 1 10 10
Design Project 1 28 28
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 150

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.15454
LO.24344
LO.35443
LO.453

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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