Course Name Code Semester T+U Hours Credit ECTS
Introduction To Bioinformatics BSM 434 8 3 + 0 3 5
Precondition Courses BMS234 Discrete Computational Structures
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Optional
Course Coordinator Doç.Dr. NİLÜFER YURTAY
Course Lecturers
Course Assistants
Course Category
Course Objective Aim of this course is to control biological data, analyze and understand them.
Course Content Moleculer biology, basic concepts. Biological data, databases. Biological array algorithms. Pattern Recognition methods. Data structures in bioinformatic. Example problem and applications.
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Manage biological data interaction with mathematics, statistics, genetic, biochemistry and computer science Lecture, Question-Answer, Discussion, Drilland Practice, Case Study, Testing, Oral Exam, Homework,
2 Use databases and manage them. Drilland Practice, Group Study, Oral Exam, Project / Design,
Week Course Topics Preliminary Preparation
1 What is the moleculer biology ? How is the biological data flow?
2 Biological databases.
3 Biological databases.
4 Biological arrays and algorithms
5 Pattern recognition methods in bioinformatic
6 Artificial neural networks
7 Markov models
8 Classification algorithms
9 Data structures
10 Suffix trees and decision trees
11 Example: protein classification
12 Example: gene definition
13 Project study
14 Project study
Resources
Course Notes [1]EBS Lecture Notes
Course Resources [2]Jones,C.,N., Pevzner,P.,A.,An introduction to Bioinformatic Algorithms,The MIT Press, 2004.
[3]R.A.Dwyer, Genomic Perl from Bioinformatics Basics to Working Code, Press Syndicate of the University of Cambridge,2003.
[4] S.I.Letovsky, Bioinformatics: Databases and Systems (Hardcover),Kluwer Akademic Publisher,1999
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 To have sufficient foundations on engineering subjects such as science and discrete mathematics, probability/statistics; an ability to use theoretical and applied knowledge of these subjects together for engineering solutions, X
2 An ability to determine, describe, formulate and solve engineering problems; for this purpose, an ability to select and apply proper analytic and modeling methods,al background in describing, formulating, modeling and analyzing the engineering problem, with a consideration for appropriate analytical solutions in all necessary situations X
3 An ability to select and use modern techniques and tools for engineering applications; an ability to use information technologies efficiently, X
4 An ability to analyze a system, a component or a process and design a system under real limits to meet desired needs; in this direction, an ability to apply modern design methods, X
5 An ability to design, conduct experiment, collect data, analyze and comment on the results and consciousness of becoming a volunteer on research, X
6 Understanding, awareness of administration, control, development and security/reliability issues about information technologies, X
7 An ability to work efficiently in multidisciplinary teams, self confidence to take responsibility, X
8 An ability to present himself/herself or a problem with oral/written techniques and have efficient communication skills; know at least one extra language, X
9 An awareness about importance of lifelong learning; an ability to update his/her knowledge continuously by means of following advances in science and technology, X
10 Understanding, practicing of professional and ethical responsibilities, an ability to disseminate this responsibility on society,
11 An understanding of project management, workplace applications, health issues of laborers, environment and job safety; an awareness about legal consequences of engineering applications, X
12 An understanding universal and local effects of engineering solutions; awareness of entrepreneurial and innovation and to have knowledge about contemporary problems.
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 50
1. Kısa Sınav 10
1. Ödev 20
1. Sözlü Sınav 10
2. Kısa Sınav 10
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 10 10
Assignment 1 15 15
Final examination 1 10 10
Total Workload 131
Total Workload / 25 (Hours) 5.24
dersAKTSKredisi 5