ECTS - Introduction to Bioinformatics

Introduction to Bioinformatics (SE446) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Introduction to Bioinformatics SE446 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives The objective of the course is to provide necessary knowledge and skills related to computational techniques for mining the large amount of biological data. In this course the applications of the computational techniques in bioinformatics will be introduced.
Course Learning Outcomes The students who succeeded in this course;
  • Apply DNA and protein sequence alignment techniques
  • Build phylogenetic trees
  • Apply techniques to predict protein structure
  • Gain skills for clustering methods used in bioinformatics
  • Analyze gene/protein networks
Course Content DNA and protein sequence alignment, phylogenetic trees, protein structure prediction, motive findin, microarray data analysis, gene/protein networks.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction Chapters 1,2,3 (main text)
2 Producing and Analyzing Sequence Alignments Chapter 4
3 Pairwise Sequence Alignment and Database Searching Chapter 5
4 Pairwise Sequence Alignment and Database Searching Chapter 5
5 Patterns, Profiles, and Multiple Alignments Chapter 6
6 Patterns, Profiles, and Multiple Alignments Chapter 6
7 Recovering Evolutionary History Chapter 7
8 Building Phylogenetic Trees Chapter 8
9 Obtaining Secondary Structure from Sequence Chapter 11
10 Predicting Secondary Structures Chapter 12
11 Modeling Protein Structure Chapter 13
12 Clustering Methods and Statistics Chapter 16
13 Clustering Methods and Statistics Chapter 16
14 Clustering Methods and Statistics Chapter 17
15 Final Examination Period Review of topics
16 Final Examination Period Review of topics

Sources

Course Book 1. M. Zvelebil and J. O. Baum, Understanding Bioinformatics, Garland Science, 2008
Other Sources 2. N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004
3. A. M. Lesk, Introduction to Bioinformatics, Oxford University Press, 2002
4. D. Mount, Bioinformatics: Sequence and genome analysis, Cold Spring Harbor Laboratory Press, 2001
5. T. Jiang, Y. Xu, and M. Zhang, eds. Current Topics in Computational Molecular Biology, MIT press, 2002

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 1 20
Presentation - -
Project 1 30
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 20
Final Exam/Final Jury 1 30
Toplam 4 100
Percentage of Semester Work 70
Percentage of Final Work 30
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Adequate knowledge in mathematics, science and computing fields; ability to apply theoretical and practical knowledge of these fields in solving engineering problems related to information systems. X
2 Ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose.
3 Ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; ability to apply modern design methods for this purpose.
4 Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in information systems engineering applications; ability to use information technologies effectively. X
5 Ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the information systems discipline.
6 Ability to work effectively in inter/inner disciplinary teams; ability to work individually. X
7 a. Effective oral and written communication skills in Turkish; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. b. Knowledge of at least one foreign language; ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8 Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development.
9 a. Ability to behave according to ethical principles, awareness of professional and ethical responsibility. b. Knowledge of the standards utilized in information systems engineering applications.
10 a. Knowledge on business practices such as project management, risk management and change management. b. Awareness about entrepreneurship, and innovation. c. Knowledge on sustainable development.
11 a. Knowledge of the effects of information systems engineering applications on the universal and social dimensions of health, environment, and safety. b. Awareness of the legal consequences of engineering solutions.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 2 32
Presentation/Seminar Prepration
Project
Report
Homework Assignments 3 5 15
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 10 20
Prepration of Final Exams/Final Jury 1 15 15
Total Workload 130