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Syllabus ( MBG 311 )


   Basic information
Course title: Introduction To Bioinformatics
Course code: MBG 311
Lecturer: Assist. Prof. Saliha İŞSEVER ÖZTÜRK
ECTS credits: 7
GTU credits: 5 (3+4+0)
Year, Semester: 3, Fall
Level of course: First Cycle (Undergraduate)
Type of course: Area Elective
Language of instruction: English
Mode of delivery: Face to face , Lab work
Pre- and co-requisites: None
Professional practice: No
Purpose of the course: The aim of the course is to introduce the students to bioinformatics dicipline. To familiarize the biological databases as well as the other biological information resources, to access the data in these resources, to teach the recent bioinformatics methods and tools besides the underlying principles that can be used in order to analyze the obtained data are among the goals of this course.
   Learning outcomes Up

Upon successful completion of this course, students will be able to:

  1. Build up knowledge about the definition, scope and history of the bioinformatics field.

    Contribution to Program Outcomes

    1. To be able to comprehend the history and nature of scientific thinking and to apply them to problems in the field.

    Method of assessment

    1. Written exam
  2. Use different kinds of biological databases and be able to search these databases and retrieve information from them.

    Contribution to Program Outcomes

    1. To be able to work individually, make independent decisions and participate actively in multidisciplinary group studies.
    2. To be able to follow current scientific and technological innovations with the awareness of continuous learning and to apply them in the field.
    3. To be able to drive hypotheses using existing knowledge, designing and conducting experiment for problem solving and make correct interpretation of the results obtained from the experiment.

    Method of assessment

    1. Written exam
    2. Homework assignment
    3. Seminar/presentation
  3. Recall pairwise and multiple sequence alignment algoritms and score matrices.

    Contribution to Program Outcomes

    1. To be able to drive hypotheses using existing knowledge, designing and conducting experiment for problem solving and make correct interpretation of the results obtained from the experiment.

    Method of assessment

    1. Written exam
    2. Homework assignment
  4. Do similarity searches and interpret the results.

    Contribution to Program Outcomes

    1. To be able to work individually, make independent decisions and participate actively in multidisciplinary group studies.
    2. To be able to drive hypotheses using existing knowledge, designing and conducting experiment for problem solving and make correct interpretation of the results obtained from the experiment.

    Method of assessment

    1. Written exam
    2. Homework assignment
  5. Do restriction analysis.

    Contribution to Program Outcomes

    1. To be able to work individually, make independent decisions and participate actively in multidisciplinary group studies.
    2. To be able to drive hypotheses using existing knowledge, designing and conducting experiment for problem solving and make correct interpretation of the results obtained from the experiment.

    Method of assessment

    1. Written exam
    2. Homework assignment
  6. Recognize and search primary and secondary protein databases (protein sequence, domain/family and structure databases).

    Contribution to Program Outcomes

    1. To be able to work individually, make independent decisions and participate actively in multidisciplinary group studies.
    2. To be able to drive hypotheses using existing knowledge, designing and conducting experiment for problem solving and make correct interpretation of the results obtained from the experiment.

    Method of assessment

    1. Written exam
    2. Homework assignment
  7. Determine physico-chemical properties and also post-translational modifications of proteins.

    Contribution to Program Outcomes

    1. To be able to work individually, make independent decisions and participate actively in multidisciplinary group studies.
    2. To be able to drive hypotheses using existing knowledge, designing and conducting experiment for problem solving and make correct interpretation of the results obtained from the experiment.

    Method of assessment

    1. Written exam
    2. Homework assignment
   Contents Up
Week 1: Introduction to the Course
Description, Scope and the History of Bioinformatics
Week 2: Examining the Important Bioinformatics Centers: NCBI, EBI, SIB
Week 3: Biological Databases
Collecting and Storage of the Sequences: Submission of the Sequences to the Databases; Sequence Formats
Week 4: Information Retrieval: Entrez Sequence Search and Information Retrieval System
Week 5: Sequence Comparison Methods I: Pairwise Sequence Alignment
Dotplot Applications
Week 6: Sequence Comparison Methods II: Database Similarity Searching
BLAST / FASTA Applications
Week 7: Sequence Comparison Methods III: Multiple Alignment Methods
CLUSTAL W, Jalview, LOGO Applications
Week 8: Classification of Proteins and Secondary Database Searching I: PROSITE, INTERPRO
Week 9: Mid-term Exam

Evaluation of the Exam and Solving the Exam Questions
Week 10: Classification of Proteins and Secondary Database Searching II: CATH, SCOP, PDB

Homework Assignment
Week 11: Protein Analysis and Proteomics: EXPASY
Week 12: Restriction Analysis: REBASE
Week 13: Primer Design
Week 14: Student Presentations
Week 15*: General Evaluation
Week 16*: Final Exam
Textbooks and materials:
Recommended readings: 1. Lesk, A. M., (2014), "Introduction to Bioinformatics", 3rd Ed., Oxford University Press.
2. Xiong, J, (2006), "Essential Bioinformatics", Cambridge University Press.
3. Mount, D. W., (2004), "Bioinformatics: Sequence and Genome Analysis", 2nd Ed., Cold Spring Harbor Laboratory Press.
4. Krawetz, S. A., Womble, D. D.,(2003), "Introduction to Bioinformatics: a Theoretical and Practical Approach. Humana Press.
5. Orengo, C. A., Jones, D. T., Thornton, J. M., (2003), "Bioinformatics: Genes, Proteins and Computers", Garland Science/BIOS Scientific Publishers.
  * Between 15th and 16th weeks is there a free week for students to prepare for final exam.
Assessment Up
Method of assessment Week number Weight (%)
Mid-terms: 9 30
Other in-term studies: 0
Project: 12 15
Homework: 10 15
Quiz: 0
Final exam: 16 40
  Total weight:
(%)
   Workload Up
Activity Duration (Hours per week) Total number of weeks Total hours in term
Courses (Face-to-face teaching): 3 14
Own studies outside class: 2 14
Practice, Recitation: 4 14
Homework: 10 1
Term project: 5 3
Term project presentation: 1 1
Quiz: 0 0
Own study for mid-term exam: 10 1
Mid-term: 2 1
Personal studies for final exam: 15 1
Final exam: 2 1
    Total workload:
    Total ECTS credits:
*
  * ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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