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Course unit
STRUCTURAL BIOINFORMATICS
SCP7079278, A.A. 2018/19
Information concerning the students who enrolled in A.Y. 2018/19
ECTS: details
Type |
Scientific-Disciplinary Sector |
Credits allocated |
Educational activities in elective or integrative disciplines |
BIO/10 |
Biochemistry |
6.0 |
Course unit organization
Period |
Second semester |
Year |
1st Year |
Teaching method |
frontal |
Type of hours |
Credits |
Teaching hours |
Hours of Individual study |
Shifts |
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 |
Examination board
Board |
From |
To |
Members of the board |
2 a.a. 2018/2019 |
01/10/2018 |
28/02/2020 |
TOSATTO
SILVIO
(Presidente)
DI SANTE
MOISES
(Membro Effettivo)
BRINI
MARISA
(Supplente)
SZABO'
ILDIKO'
(Supplente)
ZANOTTI
GIUSEPPE
(Supplente)
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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)
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Prerequisites:
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Basic knowledge of optimization methods and machine learning. Python programming language. |
Target skills and knowledge:
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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:
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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:
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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:
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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:
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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:
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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) |
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K.C. Mathews, K.E. Van Holde, K.G. Ahern, Biochimica (3° edizione). --: Casa Editrice Ambrosiana, 2004.
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Pascarella, Stefano; Paiardini, Alessandro, Bioinformaticadalla sequenza alla struttura delle proteine. Bologna: Zanichelli, 2011.
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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)
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