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Course Detail

Course Description

CourseCodeSemesterT+P (Hour)CreditECTS
BIOINFORMATICS-Fall Semester3+036
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of CourseEnglish
Course LevelFirst Cycle (Bachelor's Degree)
Course TypeElective
Course CoordinatorProf.Dr. Reda ALHAJJ
Name of Lecturer(s)Prof.Dr. Reda ALHAJJ
Assistant(s)
AimThe 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 ContentThis 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 KazanımlarıTeaching MethodsAssessment Methods
Has a general understanding of central topics and concepts within the field of bioinformaticsA, 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 algorithmsA, E, F, G
Is able to compare technical aspects of pairwise local and global sequence alignment algorithmA, E, F, G
Is able to use biological databases and knowledgebases, machine learning and network analysisA, E, F, G
Understanding of basic approaches to biological networks and visualize 5A, F, G
Teaching Methods:5: Cooperative Learning
Assessment Methods:A: Traditional Written Exam, E: Homework, F: Project Task, G: Quiz

Course Outline

OrderSubjectsPreliminary Work
1Introduction to the course material, what is bioinformatics, and why to study bioinformatics
2Building the background: Basic concepts in bioinformatics
3suffix trees and arrays
4Sequence Alignment basics
5pairwise sequence alignment
6multiple sequence alignment
7Databases and database search
8Microarray data analysis
9Presentations by students lecture/ articles / tools
10Presentations by students lecture/ articles / tools
11Phylogenetic Trees
12Machine learning, Network model and graph analysis
13Biological networks, visualization and analysis
14Project 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
NoProgram QualificationContribution Level
12345
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 LevelAbsolute Evaluation
Rate of Midterm Exam to Success 30
Rate of Final Exam to Success 70
Total 100
ECTS / Workload Table
ActivitiesNumber ofDuration(Hour)Total Workload(Hour)
Course Hours14342
Guided Problem Solving14228
Resolution of Homework Problems and Submission as a Report12020
Term Project000
Presentation of Project / Seminar12020
Quiz515
Midterm Exam14545
General Exam000
Performance Task, Maintenance Plan155
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

CourseCodeSemesterT+P (Hour)CreditECTS
BIOINFORMATICS-Fall Semester3+036
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of CourseEnglish
Course LevelFirst Cycle (Bachelor's Degree)
Course TypeElective
Course CoordinatorProf.Dr. Reda ALHAJJ
Name of Lecturer(s)Prof.Dr. Reda ALHAJJ
Assistant(s)
AimThe 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 ContentThis 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 KazanımlarıTeaching MethodsAssessment Methods
Has a general understanding of central topics and concepts within the field of bioinformaticsA, 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 algorithmsA, E, F, G
Is able to compare technical aspects of pairwise local and global sequence alignment algorithmA, E, F, G
Is able to use biological databases and knowledgebases, machine learning and network analysisA, E, F, G
Understanding of basic approaches to biological networks and visualize 5A, F, G
Teaching Methods:5: Cooperative Learning
Assessment Methods:A: Traditional Written Exam, E: Homework, F: Project Task, G: Quiz

Course Outline

OrderSubjectsPreliminary Work
1Introduction to the course material, what is bioinformatics, and why to study bioinformatics
2Building the background: Basic concepts in bioinformatics
3suffix trees and arrays
4Sequence Alignment basics
5pairwise sequence alignment
6multiple sequence alignment
7Databases and database search
8Microarray data analysis
9Presentations by students lecture/ articles / tools
10Presentations by students lecture/ articles / tools
11Phylogenetic Trees
12Machine learning, Network model and graph analysis
13Biological networks, visualization and analysis
14Project 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
NoProgram QualificationContribution Level
12345
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 LevelAbsolute Evaluation
Rate of Midterm Exam to Success 30
Rate of Final Exam to Success 70
Total 100

Numerical Data

Student Success

Ekleme Tarihi: 09/10/2023 - 10:50Son Güncelleme Tarihi: 09/10/2023 - 10:51