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Computer Engineering
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Computer Engineering Main Page / Program Curriculum / System Theory in Biophysics - I (Not offered.)

System Theory in Biophysics - I (Not offered.)

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
CSE0580 System Theory in Biophysics - I (Not offered.) 3/0/0 DE Turkish 9
Course Goals
is to train students who can work creatively at the interface between theory and experiment, and who will provide the dynamic leadership necessary for the next generation of biological research.
Prerequisite(s) An undergraduate degree in Computer Engineering or Related fields
Corequisite(s) One year each of college-level mathematics and physics; one year each of college level biology and chemistry recommended
Special Requisite(s) None
Instructor(s)
Course Assistant(s) TBA
Schedule TBA
Office Hour(s) TBA
Teaching Methods and Techniques - Lectures

- Presentations

- Projects

- Discussions
Principle Sources - Biophysical Journal : http://www.cell.com/biophysj/

 -  Network-articles

 - General bioinformatics, knowledge-representation                    

Biophysics: theory and experiment

Other Sources -

David Mount (2001): Bioinformatics. Sequence and Genome Analysis

Bourne-Weissig (2003) Structural Bioinformatics

Pain (2000) Mechanisms of Protein Folding

  Koonin-Galperin (2003): Sequence, evolution, function

Bradbury-Pongor (1999): Structural Biology and Functional Genomics

Bonholdt-Schuster (2003) : Handbook of Graphs and Networks

John F. Sowa. (2000): Knowledge Representation

Lawrence Hunter (2000): AI and Molecular Biology

Minoru Kanehisa (2000): Post-genome informatics

Dorogovtsev-Mendes (2003) Evolution of networks

Patthy (1999) Protein evolution

Course Schedules
Week Contents Learning Methods
1. Week The Statistical Mechanics of Biopolymers
2. Week The Physics of Proteins
3. Week The Physics of Chromosomes
4. Week Transport
5. Week The Physics of Membranes
6. Week Dynamical Systems
7. Week The Physics of Networks
8. Week
9. Week
10. Week
11. Week
12. Week
13. Week
14. Week
15. Week
16. Week
17. Week
Assessments
Evaluation tools Quantity Weight(%)
Midterm(s) 2 30
Homework / Term Projects / Presentations 5 50
Final Exam 1 20


Program Outcomes
PO-1an ability to apply knowledge from undergraduate and graduate engineering and other disciplines to identify, formulate, and solve novel and complex electrical/computer engineering problems that require advanced knowledge within the field
PO-2knowledge of advanced topics within at least two subdisciplines of computer engineering
PO-3the ability to understand and integrate new knowledge within the field;
PO-4the ability to apply advanced technical knowledge in multiple contexts
PO-5a recognition of the need for, and an ability to engage in, life-long learning
PO-6the ability to plan and conduct an organized and systematic study on a significant topic within the field
PO-7an ability to convey technical material through formal written reports which satisfy accepted standards for writing style
PO-8the ability to analyze and use existing literature
PO-9the ability to demonstrate effective oral communication skills
PO-10the ability to stay abreast of advancements in the area of computer engineering
Learning Outcomes
LO-1demonstrate a basic knowledge of central concepts in the biomedical sciences.
LO-2understand the current concepts in biochemistry and molecular genetics
LO-3read and critically evaluate the scientific literature.
LO-4formulate hypotheses based on current concepts in the field and design, conduct, and interpret their own research projects.
LO-5communicate research results effectively through oral presentations at scientific seminars, conferences, and other venues.
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10
LO 1
LO 2
LO 3
LO 4
LO 5