1	Course Title:	BIOINFORMATIC ALGORITHM
2	Course Code:	BM5130
3	Type of Course:	Optional
4	Level of Course:	Second Cycle
5	Year of Study:	1
6	Semester:	2
7	ECTS Credits Allocated:	6
8	Theoretical (hour/week):	3
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Doç. Dr. GIYASETTİN ÖZCAN
16	Course Lecturers:
17	Contactinformation of the Course Coordinator:	Bilgisayar Müh. Bölüm Binası, 1. kat, oda 107 Tel.:+90 (224) 294 2792 email: gozcan at uludag.edu.tr
18	Website:
19	Objective of the Course:	To learn methods and algorithms for analyzing high-volume biological data / signals. To learn how to obtain results that have meaning in medical terms with these methods.
20	Contribution of the Course to Professional Development	Understanding biological databases, making the algorithm designs necessary to process these databases

21

Learning Outcomes:

1 Students learn the algorithms which are used to analze high volüme biological data.; 2 Students learn to use probabilistic prediction methods to solve problems.; 3 In terms of medicine, students understand the benefits of the bioinformatics algorithms;

22	Course Content:

Week	Theoretical	Practical
1	Fundamental problems of bioinformatics and its computations
2	Sequence Alignment Algorithms
3	Short read sequence alignment
4	Alignment against database, BLAST
5	Multiple Sequence Alignment
6	Motif search algorithms
7	Probabilistic algorithms
8	Phylogeny Algorithms
9	Next Generation Sequencing
10	Genomic Integration
11	Biological networks
12	Secondary prediction
13	Protein structure prediction
14	Interaction with cancer drugs

23	Textbooks, References and/or Other Materials:	1. Richard Durbin, Sean R. Eddy, Anders Krogh, Graeme Mitchison Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids , 1998
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	1	25
Quiz	0	0
Homeworks, Performances	2	15
Final Exam	1	60
Total	4	100
Contribution of Term (Year) Learning Activities to Success Grade		40
Contribution of Final Exam to Success Grade		60
Total		100
Measurement and Evaluation Techniques Used in the Course	Measurement and evaluation is carried out according to the priciples of Bursa uludag University Associate and Undergraduate Education Regulation.
Information	The relative evoluation system is applied. 1 Midterm and 1 Final exams are held.

25

ECTS / WORK LOAD TABLE

Activites	NUMBER	TIME [Hour]	Total WorkLoad [Hour]
Theoretical	14	3	42
Practicals/Labs	0	0	0
Self Study and Preparation	14	4	56
Homeworks, Performances	2	0	0
Projects	0	0	0
Field Studies	0	0	0
Midtermexams	1	30	30
Others	0	0	0
Final Exams	1	52	52
Total WorkLoad			180
Total workload/ 30 hr			6
ECTS Credit of the Course			6

26	CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 PQ7 PQ8 PQ9 PQ10 LO1 5 4 3 1 1 1 0 0 0 0 LO2 4 4 4 1 1 1 0 0 0 0 LO3 1 1 4 1 1 1 0 0 0 0

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High