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 2025/2026

The 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

ModulesCreditsTAFSSD
One course to be chosen among the following:
One course to be chosen among the following

2° Year  activated in the A.Y. 2016/2017

ModulesCreditsTAFSSD
Stage
2
F
-
Prova finale
40
E
-
ModulesCreditsTAFSSD
One course to be chosen among the following:
One course to be chosen among the following
activated in the A.Y. 2016/2017
ModulesCreditsTAFSSD
Stage
2
F
-
Prova finale
40
E
-

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.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S003660

Credits

6

Language

English en

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Period

I semestre dal Oct 1, 2015 al Jan 29, 2016.

Learning outcomes

1. to learn about some basic problems and algorithms behind common bioinformatics applications (sequence alignment, sequence similarity, phylogenetics), and 2. to get an idea of some basic computational issues (problem specification, efficiency of algorithms, limitations).

Program

ALGORITHM ANALYSIS

Introduction to algorithm analysis: running time and storage space analysis; notation for complexity analysis: Big-Oh-notation, growth of functions; formalism on strings/sequences; basic combinatorics on strings;

SEQUENCE ALIGNMENT

Applications; Pairwise sequence alignment: Exhaustive search, Dynamic programming (DP) algorithm of Needleman-Wunsch (global alignment), DP algorithm of Smith-Waterman (local alignment), other variants; multiple sequence alignment: DP algorithm and heuristics; Scoring matrices: PAM (computation, application); Heuristics for sequence alignment and database search: BLAST; string distance and similarity, edit distance;

PHYLOGENETICS

Introduction to graphs and trees; number of phylogenetic trees; distance-based data: algorithm UPGMA; character-based data: Perfect Phylogeny (PP), Small parsimony: Fitch' algorithm; Large parsimony: heuristics.

Examination Methods

Written exam, followed by oral exam.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE