First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
Course unit
SC02122869, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2019/20

Information on the course unit
Degree course First cycle degree in
SC1165, Degree course structure A.Y. 2008/09, A.Y. 2019/20
bring this page
with you
Number of ECTS credits allocated 5.0
Type of assessment Evaluation
Website of the academic structure
Department of reference Department of Biology
Mandatory attendance
Language of instruction Italian
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge STEFANO TOPPO BIO/10
Other lecturers LAURA TREU BIO/11

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Other -- -- 5.0

Course unit organization
Period First semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Laboratory 2.0 32 18.0 No turn
Lecture 3.0 24 51.0 No turn

Start of activities 30/09/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2008 course timetable

Prerequisites: No prerequisites are required to attend the course unit.
Target skills and knowledge: The aim of the course unit is to allow the student to acquire some basic knowledge on Informatics and Bioinformatics.
About informatics, the course unit aims to introduce numerical systems and their history with reference to their application and implementation in modern computers. The basic concepts related to the design of an algorithm and its representation in pseudocode will also be introduced. Finally, the student will be introduced to the python programming language and common software through lectures and exercises in the computer room.

About Bioinformatics, the course will allow students to gain skills on:
• retrieving scientific data, with the introduction of some database regarding biological record and literature;
• analyzing nucleic acid and protein sequences, with 1) the description of some database that present data on sequence comparison and 2) a brief introduction on sequence similarity search.
Examination methods: Regarding informatics, the student must pass a multiple-choice test on the topics covered both in class and in the computer lab on the Python programming language.

Regarding Bioinformatics, the student must pass a multiple-choice test on the topics covered both in class and during practicals.
Assessment criteria: The written exam contains questions (multiple choice) to evaluate students’ learning level.

About Bioinformatics, the written exam will allow to test the students' acquired skills and operational ability. The exam will evaluate the ability of 1) retrieving biological information, 2) understanding the results of complex queries on database and of sequence similarity search and 3) describing what is visualized in the analyzed database.
Course unit contents: The notions related to informatics part of the course unit will be the following:
1. History and evolution of numerical systems and their implementation in modern computers
2. Concepts and basics of computer science (Von Neumann architecture)
3. Introduction to operations on binary numerical systems
4. Introduction to the algorithms and their representation in pseudocode
5. The following topics will be covered in the computer lab:
a. Programming elements using the Python language
b. Self-learning through quizzes and tests on Python
c. Creation of small programs in Python

The concepts related to Bioinformatics will be the following:
1. Brief description of different biological data types and how they are memorized in primary and secondary database. The analyzed topics describe the structural organization and the retrieval of data from some of the main bioinformatics resources available on the web, especially the resources maintained at the NCBI.
2. Genomics and metagenomics browser will be explained, as different and specific tools useful for retrieving biological data.
3. Alignment and sequence similarity searches and their applications, as a tool for studying evolution at molecular level.
The following topics will be covered in the computer lab:
a. retrieval and understanding of biological information such as scientific literature, nucleic acid and protein records, and some other records related to specific biological database.
b. sequence similarity search useful to compare nucleic acid and protein sequences.
Planned learning activities and teaching methods: The course unit consists of classroom lectures and experiences of programming and use of software applications in the computer classroom.
Additional notes about suggested reading: For the part of informatics, the slides of the lectures will be available in the moodle platform and are as a reference. For programming in Python, we will refer to parts of the book:
Downey, J. Elkner, C. Meyers. “How to Think Like a Computer Scientist: Learning With Python”
freely downloadable from

Regarding Bioinformatics, the slides of the lectures will be available in the moodle platform:
Textbooks (and optional supplementary readings)
  • Downey, J. Elkner, C. Meyers, Pensare da Informatico, Imparare con Python. Wellesley, Massachusetts: Green Tea Press, 2002. Testo scaricabile liberamente, indicato come riferimento per la programmazione in Python della parte di informatica

Innovative teaching methods: Teaching and learning strategies
  • Laboratory
  • Questioning
  • Problem solving
  • Active quizzes for Concept Verification Tests and class discussions

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)

Sustainable Development Goals (SDGs)
Quality Education