This course provides gradute level knowledge of bioinformatics by evaluation of selected topics in the field.
Course Content
This course contains; Introduction to fundamental bioinformatics,Introduction to Linux,Primary bioinformatics data formats and databeses,Scientific programming and bioinformatics workflows,Statistical İnference and data mining in bioinformatics,Sequence alignments and motif search methods,Phylogenetic tree construction and comparative genomics,Structural bioinformatics of proteins,Genome data analysis,Transcriptome data analysis,Proteome data analysis,Mıcrobiome data analysıs,Network analysis and Systems Biology,Lastest advancements and emerging topics in bioinformatics.
Dersin Öğrenme Kazanımları
Teaching Methods
Assessment Methods
Students will gain knowledge about main concepts and key methods in bioinformatics.
16, 37, 6
A, E, G
Students will be able to retrieve, organize and manage biological data. Students will learn to recognize computational challenges and describe bioinformatics problems Students will be able to comprehend related methodology and apply proper bioinformatics solutions
3, 37, 5, 6
A, E, G
Students will be able to evaluate and interpret the data analysis result. Students will learn to use appropriate terminology and report bioinformatics findings.
10, 12, 16, 37, 6
A, E, G
Students will obtain novel insights into interdisciplinary and integrative research strategies.
10, 16, 37, 6
A, E, G
Students will be able to discuss recent developments and emerging topics in bioinformatics. Students being able to follow state-of-the-art research in this interdisciplinary field.
10, 13, 14, 16, 6
A, E, G
Teaching Methods:
10: Discussion Method, 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 3: Problem Baded Learning Model, 37: Computer-Internet Supported Instruction, 5: Cooperative Learning, 6: Experiential Learning
Assessment Methods:
A: Traditional Written Exam, E: Homework, G: Quiz
Course Outline
Order
Subjects
Preliminary Work
1
Introduction to fundamental bioinformatics
2
Introduction to Linux
3
Primary bioinformatics data formats and databeses
4
Scientific programming and bioinformatics workflows
5
Statistical İnference and data mining in bioinformatics
6
Sequence alignments and motif search methods
7
Phylogenetic tree construction and comparative genomics
8
Structural bioinformatics of proteins
9
Genome data analysis
10
Transcriptome data analysis
11
Proteome data analysis
12
Mıcrobiome data analysıs
13
Network analysis and Systems Biology
14
Lastest advancements and emerging topics in bioinformatics
Resources
Understanding bioinformatics.
Published in 2008.
Marketa Zvelebil & Jeremy O. Baum.
ISBN-10: 0-8153-4024-9 (pbk.).
Garland Science, Taylor & Francis Group, LLC.
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Develop and deepen knowledge in the same or in a different field to the proficiency level based on Bachelor level qualifications.
X
2
Conceive the interdisciplinary interaction which the field is related with.
X
3
Use of theoretical and practical knowledge within the field at a proficiency level and solve the problem faced related to the field by using research methods.
X
4
Interpret the knowledge about the field by integrating the information gathered from different disciplines and formulate new knowledge.
X
5
Independently conduct studies that require proficiency in the field.
X
6
Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field.
X
7
Evaluate knowledge and skills acquired at proficiency level in the field with a critical approach and direct the learning.
X
8
Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
X
9
Define the social and environmental aspects of engineering applications.
X
10
Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and teach these values.
X
Assessment Methods
Contribution Level
Absolute Evaluation
Rate of Midterm Exam to Success
50
Rate of Final Exam to Success
50
Total
100
ECTS / Workload Table
Activities
Number of
Duration(Hour)
Total Workload(Hour)
Course Hours
0
0
0
Guided Problem Solving
0
0
0
Resolution of Homework Problems and Submission as a Report
0
0
0
Term Project
0
0
0
Presentation of Project / Seminar
0
0
0
Quiz
0
0
0
Midterm Exam
0
0
0
General Exam
0
0
0
Performance Task, Maintenance Plan
0
0
0
Total Workload(Hour)
0
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(0/30)
0
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
SELECTED TOPICS in BIOINFORMATICS
-
Spring Semester
3+0
3
8
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of Course
English
Course Level
Second Cycle (Master's Degree)
Course Type
Elective
Course Coordinator
Name of Lecturer(s)
Assist.Prof. Kıvanç KÖK
Assistant(s)
Aim
This course provides gradute level knowledge of bioinformatics by evaluation of selected topics in the field.
Course Content
This course contains; Introduction to fundamental bioinformatics,Introduction to Linux,Primary bioinformatics data formats and databeses,Scientific programming and bioinformatics workflows,Statistical İnference and data mining in bioinformatics,Sequence alignments and motif search methods,Phylogenetic tree construction and comparative genomics,Structural bioinformatics of proteins,Genome data analysis,Transcriptome data analysis,Proteome data analysis,Mıcrobiome data analysıs,Network analysis and Systems Biology,Lastest advancements and emerging topics in bioinformatics.
Dersin Öğrenme Kazanımları
Teaching Methods
Assessment Methods
Students will gain knowledge about main concepts and key methods in bioinformatics.
16, 37, 6
A, E, G
Students will be able to retrieve, organize and manage biological data. Students will learn to recognize computational challenges and describe bioinformatics problems Students will be able to comprehend related methodology and apply proper bioinformatics solutions
3, 37, 5, 6
A, E, G
Students will be able to evaluate and interpret the data analysis result. Students will learn to use appropriate terminology and report bioinformatics findings.
10, 12, 16, 37, 6
A, E, G
Students will obtain novel insights into interdisciplinary and integrative research strategies.
10, 16, 37, 6
A, E, G
Students will be able to discuss recent developments and emerging topics in bioinformatics. Students being able to follow state-of-the-art research in this interdisciplinary field.
10, 13, 14, 16, 6
A, E, G
Teaching Methods:
10: Discussion Method, 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 3: Problem Baded Learning Model, 37: Computer-Internet Supported Instruction, 5: Cooperative Learning, 6: Experiential Learning
Assessment Methods:
A: Traditional Written Exam, E: Homework, G: Quiz
Course Outline
Order
Subjects
Preliminary Work
1
Introduction to fundamental bioinformatics
2
Introduction to Linux
3
Primary bioinformatics data formats and databeses
4
Scientific programming and bioinformatics workflows
5
Statistical İnference and data mining in bioinformatics
6
Sequence alignments and motif search methods
7
Phylogenetic tree construction and comparative genomics
8
Structural bioinformatics of proteins
9
Genome data analysis
10
Transcriptome data analysis
11
Proteome data analysis
12
Mıcrobiome data analysıs
13
Network analysis and Systems Biology
14
Lastest advancements and emerging topics in bioinformatics
Resources
Understanding bioinformatics.
Published in 2008.
Marketa Zvelebil & Jeremy O. Baum.
ISBN-10: 0-8153-4024-9 (pbk.).
Garland Science, Taylor & Francis Group, LLC.
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Develop and deepen knowledge in the same or in a different field to the proficiency level based on Bachelor level qualifications.
X
2
Conceive the interdisciplinary interaction which the field is related with.
X
3
Use of theoretical and practical knowledge within the field at a proficiency level and solve the problem faced related to the field by using research methods.
X
4
Interpret the knowledge about the field by integrating the information gathered from different disciplines and formulate new knowledge.
X
5
Independently conduct studies that require proficiency in the field.
X
6
Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field.
X
7
Evaluate knowledge and skills acquired at proficiency level in the field with a critical approach and direct the learning.
X
8
Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
X
9
Define the social and environmental aspects of engineering applications.
X
10
Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and teach these values.
