BYF708 - COMPUTATIONAL BIOPHYSICS II

Course Name Code Semester Theory
(hours/week)		 Application
(hours/week)		 Credit ECTS
COMPUTATIONAL BIOPHYSICS II BYF708 Fall 2 2 3 9
PrequisitesBYF602 and BYF603
Course languageTurkish
Course typeElective 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesLecture
Discussion
Question and Answer
Other  
Instructor (s)Prof. Nuhan Puralı, Prof. Turgut BaÅŸtuÄŸ, Assoc. Prof. A. Ruhi Soylu 
Course objectiveMain objective of the course Ä°s to harness the students with the fundemental knowledge and experience for expressing the biological signals and events in mathematical equations and contruction of models working on those expressions. 
Learning outcomes
  1. Students will gain a capacity for expressing all the events, processes, and signals present in biology and medicine, in mathematical expressions partly or completely. Students will also develop an experience in constructing digital models working on the related mathematical expressions. Students will learn the system concept; the elements that comprise a system; the basic electrical principles related to simulation process; how physiological systems are modeled by electrical circuits.
  2. Students will learn that the functions of a physiological system can be explained easily by means of its electrical equivalent. Besides, they will see that the pathologies of a system can be realized by changing the values of the parameters of the system, so that there will be no need to wait for a real case to examine
Course ContentCourse is consisted of four major sections; modeling of cell, cell ensembles, organs and systems. In the first section models used for simulating electrical properties of a cell (mostly a neuron). Second session is dedicated for modeling the information transfer between a group of cell located in a neuronal circuit. In the third section function of an organ (the heart) will be modeled. The last section is devoted for modeling the body systems. Circulation system will be modeled by using mathematical equations and electrically equivalent circuit elements. 
ReferencesKoch C, Segev I (eds). Methods in neuronal modeling. MIT, 1998 Cambridge
Puralı N, Hücre elektrofizyolojisi ve görüntülemenin temelleri, Veri Medikal 2008
A Systems Approach to Biomedicine, William B. Blesser, McGraw-Hill Company, 1996
Handbook of Biomechanics and Human Movement Science, Y. Hog & R. Bartlett, Routledge Int. Handbooks, 2008.
Electromyography: Physiology, Engineering, and Non-Invasive Applications. Roberto Merletti, Philip J. Parker, Wiley and Sons, 2004
Introduction to Modelling in Physiology and Medicine. Claudio Cobelli, Ewart Carson, Elsevier-Academic Press, 2008
 

Course outline weekly

WeeksTopics
Week 1Modeling and its applications in biology and medicine. Modeling the passive properties of a cell.
Week 2Modeling an excitable cell.
Week 3Modeling an excitable cell.
Week 4Homework evaluation
Week 5Dynamics of cerebral cortical networks
Week 6Modelling the insulin-glucose control system
Week 7Vestibulo-ocular control system
Week 8A Baroreceptor Model
Week 9System concept; the elements that comprise a system
Week 10The modelling of the A-V valve and the systemic circulation
Week 11The electrical and mathematical models of the respiratory system
Week 12Problem solving.
Week 13Electromyography and modeling.
Week 14Modeling the human movement.
Week 15Preparation for the final exam
Week 16Final Exam

Assesment methods

Course activitiesNumberPercentage
Attendance1410
Laboratory00
Application1410
Field activities00
Specific practical training00
Assignments110
Presentation00
Project00
Seminar00
Midterms00
Final exam170
Total100
Percentage of semester activities contributing grade succes2950
Percentage of final exam contributing grade succes150
Total100

WORKLOAD AND ECTS CALCULATION

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 14 2 28
Laboratory 0 0 0
Application14228
Specific practical training000
Field activities000
Study Hours Out of Class (Preliminary work, reinforcement, ect)14798
Presentation / Seminar Preparation000
Project000
Homework assignment12020
Midterms (Study duration)000
Final Exam (Study duration) 15050
Total Workload4481224

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345
1. Graduates have knowledge related to the biophysical principles underlying all processes of life at the level of cell/tissue/organ/system    X
2. Has an ability use his/her higher intellectual processes such as critical thinking, problem solving decision development during his/her education period     
3. Can take part in some research activities to contribute to the solution of a problem in the field of biophysics    X
4. Awaring of the fact that biophysics is a multidisciplinary field, follows the developments in other branches of the Medical&Basic Sciences     
5. Can use computer software and laboratory equipment to produce appropriate stimulus, acquire the biological signals under the ideal conditions, quantitatively analyse the raw data    X
6. Acquired knowledge at an expertise level in statistical methods. Can choose the most suitable method for his/her research     
7. Is aware of the importance of the ethical rules and regulations and perform laboratory research as defined by the GLP, Bio-Safety principles     
8. Has the capacity of successfully preparing and presenting the report of the research work he/she takes part in, publishing at least one manuscript     
9. Follows the activities of the national&international organizations related to his/her expertise and takes part in them     
10. Shares the knowledge he/she acquired from biophysics with partners from all parts of the society; contributes to the formation of the knowledge-based society     

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest