Course Detail
Course Description
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|
BIOINFORMATICS | COE4110345 | Fall Semester | 3+0 | 3 | 6 |
Prerequisites Courses | |
Recommended Elective Courses | |
Language of Course | English |
Course Level | First Cycle (Bachelor's Degree) |
Course Type | Elective |
Course Coordinator | Prof.Dr. Reda ALHAJJ |
Name of Lecturer(s) | Prof.Dr. Reda ALHAJJ |
Assistant(s) | |
Aim | The course provides an introduction to the field of bioinformatics including key concepts, algorithms, structures and databases, the development of the field historically, its applications and relevant developments in the field. The course covers the basics of bioinformatics sequence analysis and related tools and databases. Topics covered include pairwise alignment, score matrices, sequence database search, biological networks, network analyssi and machine learning techniques, and visualization. The course also an overview of basics of molecular biology, including the concepts of genomes and genes and includes an introduction to genome browsers and central biological databases and knowledge-bases. |
Course Content | This course contains; Introduction to the course material, what is bioinformatics, and why to study bioinformatics,Building the background: Basic concepts in bioinformatics,suffix trees and arrays,Sequence Alignment basics,pairwise sequence alignment,multiple sequence alignment,Databases and database search,Microarray data analysis,Presentations by students lecture/ articles / tools ,Presentations by students lecture/ articles / tools ,Phylogenetic Trees,Machine learning, Network model and graph analysis,Biological networks, visualization and analysis,Project Presentations. |
Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
Has a general understanding of central topics and concepts within the field of bioinformatics | | A, E, F, G |
Understands dynamic programming algorithms for alignment of biological sequences | | A, E, F, G |
Understands and be able to explain basics of molecular biology and evolution pertaining to sequence alignment and connect them with the various algorithms | | A, E, F, G |
Is able to compare technical aspects of pairwise local and global sequence alignment algorithm | | A, E, F, G |
Is able to use biological databases and knowledgebases, machine learning and network analysis | | A, E, F, G |
Understanding of basic approaches to biological networks and visualize | 5 | A, F, G |
Teaching Methods: | 5: Cooperative Learning |
Assessment Methods: | A: Traditional Written Exam, E: Homework, F: Project Task, G: Quiz |
Course Outline
Order | Subjects | Preliminary Work |
---|
1 | Introduction to the course material, what is bioinformatics, and why to study bioinformatics | |
2 | Building the background: Basic concepts in bioinformatics | |
3 | suffix trees and arrays | |
4 | Sequence Alignment basics | |
5 | pairwise sequence alignment | |
6 | multiple sequence alignment | |
7 | Databases and database search | |
8 | Microarray data analysis | |
9 | Presentations by students lecture/ articles / tools | |
10 | Presentations by students lecture/ articles / tools | |
11 | Phylogenetic Trees | |
12 | Machine learning, Network model and graph analysis | |
13 | Biological networks, visualization and analysis | |
14 | Project Presentations | |
Resources |
"No specific text book, notes will be made available, including in class notes, (sometimes) slides, research papers, book chapters, etc.
Recommendaed Reference: Understanding Bioinformatics Marketa Zvelebil & Jeremy O. Baum" |
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications |
No | Program Qualification | Contribution Level |
1 | 2 | 3 | 4 | 5 |
1 | 1. An ability to apply knowledge of mathematics, science, and engineering | | | X | | |
2 | 2. An ability to identify, formulate, and solve engineering problems | | | | | X |
3 | 3. An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability | | | | X | |
4 | 4. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | | | | | X |
5 | 5. An ability to design and conduct experiments, as well as to analyze and interpret data | | | | | X |
6 | 6. An ability to function on multidisciplinary teams | X | | | | |
7 | 7. An ability to communicate effectively | | | | | X |
8 | 8. A recognition of the need for, and an ability to engage in life-long learning | | | X | | |
9 | 9. An understanding of professional and ethical responsibility | | | X | | |
10 | 10. A knowledge of contemporary issues | | | | | |
11 | 11. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context | | X | | | |
Assessment Methods
Contribution Level | Absolute Evaluation |
Rate of Midterm Exam to Success | | 30 |
Rate of Final Exam to Success | | 70 |
Total | | 100 |
ECTS / Workload Table |
Activities | Number of | Duration(Hour) | Total Workload(Hour) |
Course Hours | 14 | 3 | 42 |
Guided Problem Solving | 14 | 2 | 28 |
Resolution of Homework Problems and Submission as a Report | 1 | 20 | 20 |
Term Project | 0 | 0 | 0 |
Presentation of Project / Seminar | 1 | 20 | 20 |
Quiz | 5 | 1 | 5 |
Midterm Exam | 1 | 45 | 45 |
General Exam | 0 | 0 | 0 |
Performance Task, Maintenance Plan | 1 | 5 | 5 |
Total Workload(Hour) | 165 |
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(165/30) | 6 |
ECTS of the course: 30 hours of work is counted as 1 ECTS credit. |
Detail Informations of the Course
Course Description
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|
BIOINFORMATICS | COE4110345 | Fall Semester | 3+0 | 3 | 6 |
Prerequisites Courses | |
Recommended Elective Courses | |
Language of Course | English |
Course Level | First Cycle (Bachelor's Degree) |
Course Type | Elective |
Course Coordinator | Prof.Dr. Reda ALHAJJ |
Name of Lecturer(s) | Prof.Dr. Reda ALHAJJ |
Assistant(s) | |
Aim | The course provides an introduction to the field of bioinformatics including key concepts, algorithms, structures and databases, the development of the field historically, its applications and relevant developments in the field. The course covers the basics of bioinformatics sequence analysis and related tools and databases. Topics covered include pairwise alignment, score matrices, sequence database search, biological networks, network analyssi and machine learning techniques, and visualization. The course also an overview of basics of molecular biology, including the concepts of genomes and genes and includes an introduction to genome browsers and central biological databases and knowledge-bases. |
Course Content | This course contains; Introduction to the course material, what is bioinformatics, and why to study bioinformatics,Building the background: Basic concepts in bioinformatics,suffix trees and arrays,Sequence Alignment basics,pairwise sequence alignment,multiple sequence alignment,Databases and database search,Microarray data analysis,Presentations by students lecture/ articles / tools ,Presentations by students lecture/ articles / tools ,Phylogenetic Trees,Machine learning, Network model and graph analysis,Biological networks, visualization and analysis,Project Presentations. |
Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
Has a general understanding of central topics and concepts within the field of bioinformatics | | A, E, F, G |
Understands dynamic programming algorithms for alignment of biological sequences | | A, E, F, G |
Understands and be able to explain basics of molecular biology and evolution pertaining to sequence alignment and connect them with the various algorithms | | A, E, F, G |
Is able to compare technical aspects of pairwise local and global sequence alignment algorithm | | A, E, F, G |
Is able to use biological databases and knowledgebases, machine learning and network analysis | | A, E, F, G |
Understanding of basic approaches to biological networks and visualize | 5 | A, F, G |
Teaching Methods: | 5: Cooperative Learning |
Assessment Methods: | A: Traditional Written Exam, E: Homework, F: Project Task, G: Quiz |
Course Outline
Order | Subjects | Preliminary Work |
---|
1 | Introduction to the course material, what is bioinformatics, and why to study bioinformatics | |
2 | Building the background: Basic concepts in bioinformatics | |
3 | suffix trees and arrays | |
4 | Sequence Alignment basics | |
5 | pairwise sequence alignment | |
6 | multiple sequence alignment | |
7 | Databases and database search | |
8 | Microarray data analysis | |
9 | Presentations by students lecture/ articles / tools | |
10 | Presentations by students lecture/ articles / tools | |
11 | Phylogenetic Trees | |
12 | Machine learning, Network model and graph analysis | |
13 | Biological networks, visualization and analysis | |
14 | Project Presentations | |
Resources |
"No specific text book, notes will be made available, including in class notes, (sometimes) slides, research papers, book chapters, etc.
Recommendaed Reference: Understanding Bioinformatics Marketa Zvelebil & Jeremy O. Baum" |
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications |
No | Program Qualification | Contribution Level |
1 | 2 | 3 | 4 | 5 |
1 | 1. An ability to apply knowledge of mathematics, science, and engineering | | | X | | |
2 | 2. An ability to identify, formulate, and solve engineering problems | | | | | X |
3 | 3. An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability | | | | X | |
4 | 4. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice | | | | | X |
5 | 5. An ability to design and conduct experiments, as well as to analyze and interpret data | | | | | X |
6 | 6. An ability to function on multidisciplinary teams | X | | | | |
7 | 7. An ability to communicate effectively | | | | | X |
8 | 8. A recognition of the need for, and an ability to engage in life-long learning | | | X | | |
9 | 9. An understanding of professional and ethical responsibility | | | X | | |
10 | 10. A knowledge of contemporary issues | | | | | |
11 | 11. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context | | X | | | |
Assessment Methods
Contribution Level | Absolute Evaluation |
Rate of Midterm Exam to Success | | 30 |
Rate of Final Exam to Success | | 70 |
Total | | 100 |
Numerical Data
Ekleme Tarihi: 09/10/2023 - 10:50Son Güncelleme Tarihi: 09/10/2023 - 10:51
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