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
An ability to apply knowledge of mathematics, science, and engineering
2
An ability to identify, formulate, and solve engineering problems
X
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
An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
X
5
An ability to design and conduct experiments, as well as to analyze and interpret data
6
An ability to function on multidisciplinary teams
7
An ability to communicate effectively
8
A recognition of the need for, and an ability to engage in life-long learning
X
9
An understanding of professional and ethical responsibility
10
A knowledge of contemporary issues
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
EEE4110345
Fall Semester
3+0
3
6
Course Program
Cuma 17:30-18:15
Cuma 18:30-19:15
Cuma 19:30-20:15
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
An ability to apply knowledge of mathematics, science, and engineering
2
An ability to identify, formulate, and solve engineering problems
X
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
An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
X
5
An ability to design and conduct experiments, as well as to analyze and interpret data
6
An ability to function on multidisciplinary teams
7
An ability to communicate effectively
8
A recognition of the need for, and an ability to engage in life-long learning
X
9
An understanding of professional and ethical responsibility
10
A knowledge of contemporary issues
11
The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context
