First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
Course unit
INP8084204, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2018/19

Information on the course unit
Degree course Second cycle degree in
IN2371, Degree course structure A.Y. 2017/18, A.Y. 2018/19
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Degree course track ICT FOR LIFE AND HEALTH [004PD]
Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination STRUCTURAL BIOINFORMATICS
Department of reference Department of Information Engineering
Mandatory attendance No
Language of instruction English
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 DAMIANO PIOVESAN BIO/10
Other lecturers MOISES DI SANTE BIO/10

Course unit code Course unit name Teacher in charge Degree course code

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines INF/01 Computer Science 6.0

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

Type of hours Credits Teaching
Hours of
Individual study
Practice 2.0 16 34.0 No turn
Lecture 4.0 32 68.0 No turn

Start of activities 25/02/2019
End of activities 14/06/2019
Show course schedule 2019/20 Reg.2019 course timetable

Examination board
Board From To Members of the board
2 a.a. 2018/2019 01/10/2018 28/02/2020 PIOVESAN DAMIANO (Presidente)
DI SANTE MOISES (Membro Effettivo)
BRINI MARISA (Supplente)
SZABO' ILDIKO' (Supplente)
1 a.a. 2017/2018 01/10/2017 28/02/2019 TOSATTO SILVIO (Presidente)
BRINI MARISA (Membro Effettivo)
CALI' TITO (Membro Effettivo)
SZABO' ILDIKO' (Membro Effettivo)
ZANOTTI GIUSEPPE (Membro Effettivo)

Prerequisites: Basic knowledge of optimization methods and machine learning. Python programming language.
Target skills and knowledge: The course intends to communicate basic knowledge on structure and function of living material as well as the main computational methods for its study. Moreover, it intends to enable the student to autonomously develop a research project in structural bioinformatics, defining the state of the art for an open problem and providing an attempt to solve it through the extension of existing software libraries and the critical evaluation of obtained results.
Examination methods: The exam covers three separate parts, which have to be all passed: (relative weights in parenthesis)
1) Written test of the biochemistry concepts (ca. 30%)
2) Software project (ca. 40%)
3) Project presentation and critical evaluation (ca. 30%)
Assessment criteria: 1) understanding of concepts and algorithms presented in class
2) the ability to apply the described concepts on real problems
3) the critical capacity of being able to use the methods in the most appropriate ways, choosing between the alternatives
4) the ability to develop reusable software by extending existing libraries
5) the ability for critical presentation and discussion
Course unit contents: The course consists of two parts:
1) Introduction to living matter (2 credits):
1.1) Introduction to organic chemistry, weak interactions and energy
1.2) Structure and function of DNA and proteins
1.3) Lipids, membranes and cellular transport
1.4) Experimental methods for structure determination

2) Computational Biochemistry (4 credits):
2.1) Biological Databases
2.2) Software libraries and concepts for sequence alignments and database searches
2.3) Sequence - structure relationship in proteins and structural classification
2.4) Methods for the prediction of protein structure from sequence, the CASP experiment
2.5) Methods for the prediction of protein function and interactions, the CAFA experiment
2.6) Non-globular proteins, disorder and structural repeats
Planned learning activities and teaching methods: The course consists of lectures, practical computer exercises, lecture note contribution and the development of a project and presentation of the same with critical discussion. The exercises are intended to familiarize the student with software libraries to use for a bioinformatics project on a current problem differentiated for each group. The project presentation will require a discussion in which to bring out the strengths and weakness of the implemented software.
Additional notes about suggested reading: Many materials for the course are made available on the E-learning site. These include the transparencies of the course (as soon as available), lecture notes and literature used for the projects. The lecture notes can be downloaded in PDF format containing over 300 pages to facilitate the study.
Textbooks (and optional supplementary readings)
  • K.C. Mathews, K.E. Van Holde, K.G. Ahern, Biochimica (3° edizione). --: Casa Editrice Ambrosiana, 2004. Cerca nel catalogo
  • Pascarella, Stefano; Paiardini, Alessandro, Bioinformaticadalla sequenza alla struttura delle proteine. Bologna: Zanichelli, 2011. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Laboratory
  • Problem solving
  • Loading of files and pages (web pages, Moodle, ...)

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

Sustainable Development Goals (SDGs)
Quality Education Industry, Innovation and Infrastructure