Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Molecular and Medical Biotechnology - Enrollment from 2025/2026The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
Modules | Credits | TAF | SSD |
---|
Two courses among the following
Three courses among the following
One course among the following
One course among the following
2° Year activated in the A.Y. 2023/2024
Modules | Credits | TAF | SSD |
---|
Modules | Credits | TAF | SSD |
---|
Two courses among the following
Three courses among the following
One course among the following
One course among the following
Modules | Credits | TAF | SSD |
---|
Modules | Credits | TAF | SSD |
---|
2 courses among the following ("BIOTECHNOLOGY IN NEUROSCIENCE" 1ST YEAR; "CLINICAL PROTEOMICS" 1ST and2ND YEAR; the other courses 2nd year only)
Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Computational Biology (2022/2023)
Teaching code
4S003658
Teacher
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
BIO/10 - BIOCHEMISTRY
Period
Semester 2 dal Mar 6, 2023 al Jun 16, 2023.
Learning objectives
This course gives an introduction to molecular computational biology and to the rational design of proteins using computational techniques. The arguments of the course include: molecular dynamis simulation techniques and advanced protein bioinformatics concepts. At the end of the course the student should be able to: - Deep and critical understanding of a scientific article where computational techniques are used - Introduce (in silico) mutants able to affect the protein structure and/or function - Prepare and run molecular dynamis simulations.
Prerequisites and basic notions
There are no prerequisites
Program
Part A – Bioinformatics
− Advanced Structural Bioinformatics
- Thermodynamic basis of the stability of folded biomolecular structure
− Molecular basis of human perception
Part B – Molecular Modeling
− Basic elements of molecular modeling
− Electrostatic modeling
− Energy minimization based on force fields
− Molecular dynamics: solution by using the open source NAMD and/or Gromacs codes
− Conformational analysis
Part C – Ligand-prtoein interactions
− Protein assembly (protein-protein complexes, protein-protein interactions in protein dimers, crystals): protein-protein docking algorithms and programs
− Ligand Protein interaction: docking algorithms and programs
− Projects: Drug and/or protein design
Bibliography
Didactic methods
During the course different teaching techniques are used:
- Classical theoretical lessons
- Practical exercises on the PC (use of state-of-the-art programs for running molecular dynamics simulations, docking, and drug design)
- Literature analysis
Learning assessment procedures
Written.
The examination is divide in two parts: the first consists in the presentation (in groups) of a scientific article in which state of the arte techniques are used.
The second part is a written examination with open questions regarding the arguments of the course.
Evaluation criteria
The student must: -be able to master the specific language of modern computational biology. -be able to critically understand a scientific article in the field of computational biology -Know the theoretical basis of molecular dynamics and virtual docking
Criteria for the composition of the final grade
The final grade consists of: - Grade of the presentations to groups of high-impact scientific articles - Grade of the written exam during the exam session
Exam language
Inglese