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Syllabus ( BSB 612 )

   Basic information
Course title: Systems Neuroscience
Course code: BSB 612
Lecturer: 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: none
Professional practice: No
Purpose of the course: (i) to enable students acquire fundamental details of neurobiology, (ii) to acquire the skills for practical work on computational systems neurobiology, (iii) to acquire skills for the analysis and reproduction of computational parts of research articles on systems neuroscience
   Learning outcomes Up

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

  1. analyze intercellular and intracellular interactions in nervous system via computational systems-biology methods

    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. Apply modelling approaches to cellular networks.
    4. Identify the changes in cellular and molecular mechanisms in health and disease from the perspective of bioinformatics and systems biology.
    5. Formulate, code, solve and analyze problems on biomolecular interactions by using an engineering viewpoint.
    6. Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results.
    7. Link the concepts belonging to the different disciplines and interpret & analyze scientific research in these disciplines.
    8. Acquire scientific knowledge and work independently
    9. Effectively express his/her research ideas and findings both orally and in writing

    Method of assessment

    1. Written exam
    2. Seminar/presentation
    3. Term paper
  2. Process and interpret genome-scale data for brain related diseases (brain tumors, neurodegenerative diseases) by using computational methods

    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. Identify the changes in cellular and molecular mechanisms in health and disease from the perspective of bioinformatics and systems biology.
    4. Effectively express his/her research ideas and findings both orally and in writing
    5. 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. Written exam
    2. Term paper
  3. Identify neurobiological, neurochemical, neurodevelopmental and organizational characteristics of nervous system at cellular and molecular level

    Contribution to Program Outcomes

    1. Define and manipulate basic and advanced concepts in the field of Bioinformatics and Systems Biology
    2. Identify the changes in cellular and molecular mechanisms in health and disease from the perspective of bioinformatics and systems biology.
    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. Written exam
   Contents Up
Week 1: Introduction to Systems Neurobiology, Basics of Cellular Neurobiology
Week 2: Functional and spatial organization of brain as a system
Week 3: Basics of Neurochemistry, Brain Metabolism, Neurodevelopment
Project I
Week 4: Cell types in brain (neuron, glia), intercellular and intracellular interactions in nervous system
Quiz
Week 5: Glial Cells in Brain, Functions and Interactions
Week 6: Brain Connectomics, Interconnection of neurons, information transfer in brain
Week 7: Networks in Brain for cognitive functions and behavioral tasks (vision, memory, perception)
Quiz
Week 8: Neuro-omics: Transcriptome, Proteome, Metabolome and Interactome approaches for nervous system
Week 9: Case Study I-Brain Tumors: Molecular mechanisms, systems biology approaches
Week 10: Case Study I-Brain Tumors: Statistical inference of interactions via genome-scale datasets
Quiz
Week 11: Case Study II-Neural Stem Cells: Molecular mechanisms of stem cells, systems biology approaches
Project II
Week 12: Case Study II-Neural Stem Cells: Modeling of metabolic interactions
Homework I
Week 13: Case Study III-Neurodegenerative Diseases: Molecular mechanisms, systems biology approaches
Quiz
Week 14: Case Study III-Neurodegenerative Diseases: Modeling of protein-protein interactions
Week 15*: General Overview
Week 16*: Project III
Textbooks and materials:
Recommended readings: 1) N. Le Novere (Eds.), "Computational Systems Neurobiology", Springer, 2012

2) S. Brady, G. Siegel, R.W. Albers, D. Price, "Basic Neurochemistry: Principles of Molecular, Cellular and Medical Neurobiology", Academic Press, 8th Edition, 2011
  * 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: 3, 11, 16 60
Homework: 12 10
Quiz: 4, 7, 10,13 30
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: 4 13
Practice, Recitation: 0 0
Homework: 8 1
Term project: 7 11
Term project presentation: 3 1
Quiz: 0.5 3
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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