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Syllabus ( BSB 513 )


   Basic information
Course title: Fundamentals of Systems Biology
Course code: BSB 513
Lecturer: Assoc. Prof. Dr. Tunahan ÇAKIR
ECTS credits: 7.5
GTU credits: 3 (3+0+0)
Year, Semester: 1/2, Fall and Spring
Level of course: Second Cycle (Master's)
Type of course: Compulsory
Language of instruction: English
Mode of delivery: Face to face , Lab work
Pre- and co-requisites: none
Professional practice: No
Purpose of the course: This course is based on two key constituents of systems biology: genome-scale data and cellular networks. Within this context, experimental methods used to collect genome-scale data are covered in the course. Basic computational methods to analyze and interpret such data are also detailed, with practical examples.
   Learning outcomes Up

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

  1. Apply the techniques used to collect high-throughput omics data, which consists of the experimental part of systems biology

    Contribution to Program Outcomes

    1. Define and manipulate basic and advanced concepts in the field of Bioinformatics and Systems Biology
    2. Process and analyze genome-scale biological data using statistical methods and data mining methods.
    3. Develop an awareness of continuous learning in relation with modern technology

    Method of assessment

    1. Written exam
    2. Homework assignment
    3. Term paper
  2. Apply major statistics methods and data mining methods on the biological data by using a programming platform

    Contribution to Program Outcomes

    1. Define and manipulate basic and advanced concepts in the field of Bioinformatics and Systems Biology
    2. Process and analyze genome-scale biological data using statistical methods and data mining methods.
    3. Formulate, code, solve and analyze problems on biomolecular interactions by using an engineering viewpoint.
    4. Find out new methods to improve his/her knowledge.

    Method of assessment

    1. Written exam
    2. Homework assignment
    3. Term paper
  3. List the biological foundations of cellular networks

    Contribution to Program Outcomes

    1. Define and manipulate basic and advanced concepts in the field of Bioinformatics and Systems Biology
    2. Apply modelling approaches to cellular networks.
    3. Formulate, code, solve and analyze problems on biomolecular interactions by using an engineering viewpoint.

    Method of assessment

    1. Written exam
    2. Homework assignment
    3. Term paper
   Contents Up
Week 1: - Fundamentals of Systems Biology: Basic Concepts (systems biology, molecular biology)
- From DNA to Proteins : chromosomes, genes, gene expression, protein synthesis, folding
Week 2: Cellular Networks: Metabolic reaction networks, Gene-regulatory networks, Signalling networks
Week 3: Cellular Networks and Graph Theory, Use of Cytoscape
Quiz
Week 4: Experimental techniques of genome sciences I: Genomics, Transcriptomics
Homework
Week 5: Experimental techniques of genome sciences II: Proteomics, Metabolomics, Fluxomics, Interactomics
Quiz
Week 6: Normalization of Raw Omics Data, Methods and Challenges
Homework
Week 7: Statistical Significance Tests I: Parametric and nonparametric significance tests, ROC Curves
Quiz
Week 8: Statistical Significance Tests II: Use of MATLAB for Gene Expression Omnibus database, Gene Ontology (GO) Analysis
Homework
Week 9: - Similarity Tests : Parametric and nonparametric similarity tests
- Clustering techniques
Quiz
Week 10: Unsupervised Dimension-reduction techniques I: Principal Component Analysis Basics
Homework
Week 11: Unsupervised Dimension-reduction techniques II: Principal Component Analysis, Independent Component Analysis, and application to genome-scale data
Quiz
Week 12: Supervised Dimension-reduction techniques: Fisher Discriminant Analysis, Support Vector Machines
Homework
Project Assignment
Week 13: Cell metabolism and modeling techniques I: Enzyme kinetics, Dynamic metabolic models, Lin-log kinetic approximation
Quiz
Week 14: Cell metabolism and modeling techniques II: Flux Balance Analysis, Flux Variability Analysis
Homework
Week 15*: -
Week 16*: Project Presentations
Textbooks and materials: 1. Edda Klipp, Wolfram Liebermeister, Cristoph Wierling, Axel Kowald, Hans Lehrach, Ralf Herwig. “Systems Biology”, Wiley-Blackwell, 2009.
Recommended readings: 1. Brian P. Ingalls, "Mathematical Modeling in Systems Biology: An Introduction", The MIT Press, 2013
  * 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: 0
Other in-term studies: 0
Project: 12-16 25
Homework: 4,6,8,10,12,14 40
Quiz: 3, 5, 7, 9, 11, 13 35
Final exam: 0
  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: 5 14
Practice, Recitation: 0 0
Homework: 5 9
Term project: 8 3
Term project presentation: 1 1
Quiz: 0.5 6
Own study for mid-term exam: 0 0
Mid-term: 0 0
Personal studies for final exam: 0 0
Final exam: 0 0
    Total workload:
    Total ECTS credits:
*
  * ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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