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Syllabus ( BSB 613 )


   Basic information
Course title: Genome Scale Metabolic Models
Course code: BSB 613
Lecturer: Assoc. Prof. Dr. Tunahan ÇAKIR
ECTS credits: 7.5
GTU credits: 3 (3+0+0)
Year, Semester: 1/2, Spring
Level of course: Second Cycle (Master's)
Type of course: Area Elective
Language of instruction: English
Mode of delivery: Face to face
Pre- and co-requisites: BSB 513, BSB 515
Professional practice: No
Purpose of the course: This applied course has the following focus: (i) modeling of genome-scale metabolic networks, and (ii) integrative analysis of gneome-scale metabolic networks and omics data
   Learning outcomes Up

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

  1. Apply constraint-based modeling to genome-scale metabolic 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. Grasp the importance of bioinformatics and systems biology based viewpoint in the analysis and interpretation of working principles of the cell.

    Method of assessment

    1. Homework assignment
    2. Laboratory exercise/exam
    3. Term paper
  2. Apply the approaches to integratively analyze genomic, transcriptomic, proteomic and metabolomic data with genome-scale metabolic networks

    Contribution to Program Outcomes

    1. Process and analyze genome-scale biological data using statistical methods and data mining methods.
    2. Apply modelling approaches to cellular networks.
    3. Grasp the importance of bioinformatics and systems biology based viewpoint in the analysis and interpretation of working principles of the cell.

    Method of assessment

    1. Homework assignment
    2. Laboratory exercise/exam
    3. Term paper
  3. Construct mass-balance based models for metabolic networks

    Contribution to Program Outcomes

    1. Process and analyze genome-scale biological data using statistical methods and data mining methods.
    2. Grasp the importance of bioinformatics and systems biology based viewpoint in the analysis and interpretation of working principles of the cell.

    Method of assessment

    1. Homework assignment
    2. Laboratory exercise/exam
   Contents Up
Week 1: Crucial pathways of metabolism, precursor metabolites, defining a biomass reaction
Week 2: Basics of constraint-based modeling of metabolism: Metabolic Flux Analysis (MFA)
Homework
Week 3: Computational methods in constraint-based modeling of metabolism: Flux balance analysis (FBA), application to small-scale metabolic networks
Week 4: Computational methods in constraint-based modeling of metabolism: Flux variability analysis (FVA), application to small-scale metabolic networks
Quiz
Homework
Week 5: - Flux balance analysis, Flux variability analysis and application to genome-scale metabolic networks
- Alternative approaches in contraint-based modeling: Sampling the solution space
- sbml data format
Week 6: Overview of early FBA-based scientific articles
Homework
Week 7: Software packages in constraint-based modeling: COBRA, OptFlux, CellNet Analyzer, PySCeS CBMPy
Quiz
Week 8: Reconstruction of genome-scale metabolic networks: SEED and Raven
Homework
Week 9: GEO Transkriptome database
Prediction of metabolic fluxes for deficient cells: MOMA and ROOM approaches
Week 10: Integration of genome-scale metabolic networks with transcriptome and proteome data: GIMME, MADE, E-flux and MADE approaches
Homework
Week 11: Integration of genome-scale metabolic networks with transcriptome and proteome data: newer computational methods and comparison of the methods
Quiz
Week 12: - thermodynamic constraints in genome-scale metabolic networks
- Integration of genome-scale metabolic networks with metabolome data
Homework
Week 13: Identification of drug target candidates by constraint-based modeling of genome-scale metabolic networks: enzyme-based, metabolite-based and synergistic drug targets
Quiz
Week 14: Graph-based investigation of genome-scale metabolic networks and graph-based integration with omics data
Homework
Project Assignment
Week 15*: --
Week 16*: Final Exam
Textbooks and materials:
Recommended readings: B. Palsson, "Systems Biology: Constraint-based Reconstruction and Analysis", 2nd Edition (2015)

M. Covert, "Fundamentals of Systems Biology: From Synthetic Circuits to Whole-cell Models", (2014)
  * 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: 14 20
Homework: 2,4,6,8,10,12,14 50
Quiz: 4,7,11,13 15
Final exam: 14-16 15
  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: 3 14
Practice, Recitation: 0 0
Homework: 7 12
Term project: 12 1
Term project presentation: 0 0
Quiz: 0 0
Own study for mid-term exam: 0 0
Mid-term: 0 0
Personal studies for final exam: 6 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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