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Course Description

CourseCodeSemesterT+P (Hour)CreditECTS
COMPUTATIONAL BIOPHYSICS : TOOLS and METHODS-Spring Semester3+038
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of CourseEnglish
Course LevelSecond Cycle (Master's Degree)
Course TypeElective
Course CoordinatorAssoc.Prof. Özge ŞENSOY
Name of Lecturer(s)Assoc.Prof. Özge ŞENSOY
Assistant(s)
AimIt is aimed to teach the students some widely-used computational techniques such as molecular modeling, molecular docking and molecular dynamics simulations along with the parameters used to optimize simulations. In this way, students are expected to run a molecular dynamics simulation by their own.
Course ContentThis course contains; Introduction to Quantum Chemistry ,An overview to the Quantum Chemical Methods ,Introduction to Statistical Mechanics ,Molecular Dynamics,Force Fields ,Solvation Models,Electrostatics in Molecular dynamics,Free Energy Calculations,Enhanced Sampling Techniques ,Hybrid Simulation Methods : QM/MM calculations ,Coarse Grained Potentials /Transferability of the Coarse Grained Potentials,Molecular Docking ,Application of above-mentioned techniques to biological problems -I ,Application of above-mentioned techniques to biological problems -II.
Dersin Öğrenme KazanımlarıTeaching MethodsAssessment Methods
1) Different aspects between molecular mechanics and quantum mechanics are understood and the student can decide which method is appropriate for solving a given biological problem. 10, 13, 14, 16, 19, 2, 21, 37F
2) The student gains knowledge on the force-fields as well as water models which are needed to perform a molecular dynamics simulation. In this way, the student can decide him/herself to appropriate parameter set. 10, 13, 14, 16, 19, 2, 9F
3) At the end of the course, the student gains knowledge on how to run molecular dynamics simulations using parallel-computing systems.10, 14, 16, 2, 6, 9
4) At the end of the course, the student gains ability to perform molecular dynamics simulation and to analyze the resulting trajectory by her/his own. 10, 14, 16, 19, 2, 20, 6F
Teaching Methods:10: Discussion Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 19: Brainstorming Technique, 2: Project Based Learning Model, 20: Reverse Brainstorming Technique, 21: Simulation Technique, 37: Computer-Internet Supported Instruction, 6: Experiential Learning, 9: Lecture Method
Assessment Methods:F: Project Task

Course Outline

OrderSubjectsPreliminary Work
0Introduction to Quantum Chemistry
1An overview to the Quantum Chemical Methods
2Introduction to Statistical Mechanics
3Molecular Dynamics
4Force Fields
5Solvation Models
6Electrostatics in Molecular dynamics
7Free Energy Calculations
8Enhanced Sampling Techniques
9Hybrid Simulation Methods : QM/MM calculations
10Coarse Grained Potentials /Transferability of the Coarse Grained Potentials
11Molecular Docking
12Application of above-mentioned techniques to biological problems -I
13Application of above-mentioned techniques to biological problems -II
Resources
Frenkel and Smit, Understanding Molecular Simulation : From Algorithms to Applications, , Academic Press, Computational Science Series Sunum
1) Frenkel and Smit, Understanding Molecular Simulation : From Algorithms to Applications, , Academic Press, Computational Science Series 2)Allen and Tildesley, Computer Simulation of Liquids, Clarendon Press 3)Zhou, Molecular Modeling at the Atomic Scale, CRC Press, Taylor & Francis.

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
NoProgram QualificationContribution Level
12345
1
Develop and deepen knowledge in the same or in a different field to the proficiency level based on Bachelor level qualifications.
X
2
Conceive the interdisciplinary interaction which the field is related with.
X
3
Use of theoretical and practical knowledge within the field at a proficiency level and solve the problem faced related to the field by using research methods.
X
4
Interpret the knowledge about the field by integrating the information gathered from different disciplines and formulate new knowledge.
X
5
Independently conduct studies that require proficiency in the field.
X
6
Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field.
X
7
Evaluate knowledge and skills acquired at proficiency level in the field with a critical approach and direct the learning.
X
8
Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
X
9
Define the social and environmental aspects of engineering applications.
X
10
Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and teach these values.
X

Assessment Methods

Contribution LevelAbsolute Evaluation
Rate of Midterm Exam to Success 50
Rate of Final Exam to Success 50
Total 100
ECTS / Workload Table
ActivitiesNumber ofDuration(Hour)Total Workload(Hour)
Course Hours14342
Guided Problem Solving6318
Resolution of Homework Problems and Submission as a Report5420
Term Project000
Presentation of Project / Seminar14040
Quiz000
Midterm Exam12020
General Exam19090
Performance Task, Maintenance Plan000
Total Workload(Hour)230
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(230/30)8
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.

Detail Informations of the Course

Course Description

CourseCodeSemesterT+P (Hour)CreditECTS
COMPUTATIONAL BIOPHYSICS : TOOLS and METHODS-Spring Semester3+038
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of CourseEnglish
Course LevelSecond Cycle (Master's Degree)
Course TypeElective
Course CoordinatorAssoc.Prof. Özge ŞENSOY
Name of Lecturer(s)Assoc.Prof. Özge ŞENSOY
Assistant(s)
AimIt is aimed to teach the students some widely-used computational techniques such as molecular modeling, molecular docking and molecular dynamics simulations along with the parameters used to optimize simulations. In this way, students are expected to run a molecular dynamics simulation by their own.
Course ContentThis course contains; Introduction to Quantum Chemistry ,An overview to the Quantum Chemical Methods ,Introduction to Statistical Mechanics ,Molecular Dynamics,Force Fields ,Solvation Models,Electrostatics in Molecular dynamics,Free Energy Calculations,Enhanced Sampling Techniques ,Hybrid Simulation Methods : QM/MM calculations ,Coarse Grained Potentials /Transferability of the Coarse Grained Potentials,Molecular Docking ,Application of above-mentioned techniques to biological problems -I ,Application of above-mentioned techniques to biological problems -II.
Dersin Öğrenme KazanımlarıTeaching MethodsAssessment Methods
1) Different aspects between molecular mechanics and quantum mechanics are understood and the student can decide which method is appropriate for solving a given biological problem. 10, 13, 14, 16, 19, 2, 21, 37F
2) The student gains knowledge on the force-fields as well as water models which are needed to perform a molecular dynamics simulation. In this way, the student can decide him/herself to appropriate parameter set. 10, 13, 14, 16, 19, 2, 9F
3) At the end of the course, the student gains knowledge on how to run molecular dynamics simulations using parallel-computing systems.10, 14, 16, 2, 6, 9
4) At the end of the course, the student gains ability to perform molecular dynamics simulation and to analyze the resulting trajectory by her/his own. 10, 14, 16, 19, 2, 20, 6F
Teaching Methods:10: Discussion Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 19: Brainstorming Technique, 2: Project Based Learning Model, 20: Reverse Brainstorming Technique, 21: Simulation Technique, 37: Computer-Internet Supported Instruction, 6: Experiential Learning, 9: Lecture Method
Assessment Methods:F: Project Task

Course Outline

OrderSubjectsPreliminary Work
0Introduction to Quantum Chemistry
1An overview to the Quantum Chemical Methods
2Introduction to Statistical Mechanics
3Molecular Dynamics
4Force Fields
5Solvation Models
6Electrostatics in Molecular dynamics
7Free Energy Calculations
8Enhanced Sampling Techniques
9Hybrid Simulation Methods : QM/MM calculations
10Coarse Grained Potentials /Transferability of the Coarse Grained Potentials
11Molecular Docking
12Application of above-mentioned techniques to biological problems -I
13Application of above-mentioned techniques to biological problems -II
Resources
Frenkel and Smit, Understanding Molecular Simulation : From Algorithms to Applications, , Academic Press, Computational Science Series Sunum
1) Frenkel and Smit, Understanding Molecular Simulation : From Algorithms to Applications, , Academic Press, Computational Science Series 2)Allen and Tildesley, Computer Simulation of Liquids, Clarendon Press 3)Zhou, Molecular Modeling at the Atomic Scale, CRC Press, Taylor & Francis.

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
NoProgram QualificationContribution Level
12345
1
Develop and deepen knowledge in the same or in a different field to the proficiency level based on Bachelor level qualifications.
X
2
Conceive the interdisciplinary interaction which the field is related with.
X
3
Use of theoretical and practical knowledge within the field at a proficiency level and solve the problem faced related to the field by using research methods.
X
4
Interpret the knowledge about the field by integrating the information gathered from different disciplines and formulate new knowledge.
X
5
Independently conduct studies that require proficiency in the field.
X
6
Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field.
X
7
Evaluate knowledge and skills acquired at proficiency level in the field with a critical approach and direct the learning.
X
8
Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
X
9
Define the social and environmental aspects of engineering applications.
X
10
Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and teach these values.
X

Assessment Methods

Contribution LevelAbsolute Evaluation
Rate of Midterm Exam to Success 50
Rate of Final Exam to Success 50
Total 100

Numerical Data

Student Success

Ekleme Tarihi: 24/12/2023 - 02:47Son Güncelleme Tarihi: 24/12/2023 - 02:47