Computational Biophysics
A.Y. 2020/2021
Learning objectives
The course will teach the techniques and the algorithms to study kinetic and equilibrium properties of classical models of molecules and polymers, mainly of biological interest.
Expected learning outcomes
The student at the end of the course will have these abilities:
1. Understand the theory that controls moleclar dynamics simulations
2. To perform molecular dynamics simulations
3. To understand the algorithms to calculate free energies in biomolecular systems
4. To be able to deal with data analysis through simple scripts
1. Understand the theory that controls moleclar dynamics simulations
2. To perform molecular dynamics simulations
3. To understand the algorithms to calculate free energies in biomolecular systems
4. To be able to deal with data analysis through simple scripts
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
BIO/10 - BIOCHEMISTRY
FIS/03 - PHYSICS OF MATTER
INF/01 - INFORMATICS
FIS/03 - PHYSICS OF MATTER
INF/01 - INFORMATICS
Lessons: 42 hours
Professor:
Tiana Guido
Professor(s)