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 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 | Adequate knowledge in mathematics, science and subjects specific to the Materials Engineering; the ability to apply theoretical and practical knowledge of these areas to solve complex engineering problems and to model and solve of materials systems | X | ||||
| 2 | Understanding of science and engineering principles related to the structures, properties, processing and performance of Materials systems | |||||
| 3 | Ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose | X | ||||
| 4 | Ability to design and choose proper materials for a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design and materials selection methods for this purpose | X | ||||
| 5 | Ability to develop, select and utilize modern techniques and tools essential for the analysis and solution of complex problems in Materails Engineering applications; the ability to utilize information technologies effectively | X | ||||
| 6 | Ability to design and conduct experiments, collect data, analyse and interpret results using statistical and computational methods for complex engineering problems or research topics specific to Materials Engineering | X | ||||
| 7 | Ability to work effectively in inter/inner disciplinary teams; ability to work individually | X | ||||
| 8 | Effective oral and written communication skills in Turkish; knowlegde of at least one foreign language; the 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 | |||||
| 9 | Recognition of the need for lifelong learning; the ability to access information; follow recent developments in science and technology with continuous self-development | X | ||||
| 10 | Ability to behave according to ethical principles, awareness of professional and ethical responsibility; knowledge of standards used in engineering applications | X | ||||
| 11 | Knowledge on business practices such as project management, risk management and change management; awareness in entrepreneurship and innovativeness; knowledge of sustainable development | X | ||||
| 12 | Knowledge of the effects of Materials Engineering applications on the universal and social dimensions of health, environment and safety, knowledge of modern age problems reflected on engineering; awareness of legal consequences of engineering solutions | X | ||||
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 | ||