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 | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| 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;
|
| 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 | An ability to apply advanced knowledge of computing and/or informatics to solve software engineering problems. | |||||
| 2 | Develop solutions using different technologies, software architectures and life-cycle approaches. | |||||
| 3 | An ability to design, implement and evaluate a software system, component, process or program by using modern techniques and engineering tools required for software engineering practices. | |||||
| 4 | An ability to gather/acquire, analyze, interpret data and make decisions to understand software requirements. | |||||
| 5 | Skills of effective oral and written communication and critical thinking about a wide range of issues arising in the context of working constructively on software projects. | |||||
| 6 | An ability to access information in order to follow recent developments in science and technology and to perform scientific research or implement a project in the software engineering domain. | |||||
| 7 | An understanding of professional, legal, ethical and social issues and responsibilities related to Software Engineering. | |||||
| 8 | Skills in project and risk management, awareness about importance of entrepreneurship, innovation and long-term development, and recognition of international standards of excellence for software engineering practices standards and methodologies. | |||||
| 9 | An understanding about the impact of Software Engineering solutions in a global, environmental, societal and legal context while making decisions. | |||||
| 10 | Promote the development, adoption and sustained use of standards of excellence for software engineering practices. | |||||
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 | ||