OBSOLETE PAGE
view the updated version














Course unit
STRUCTURAL BIOINFORMATICS
SCP7079278, A.A. 2017/18

Information on the course unit
Degree course Second cycle degree in
DATA SCIENCE
SC2377, Regulation 2017/18, A.Y. 2017/18
1160958
Number of ECTS credits allocated 6.0
Course unit English denomination STRUCTURAL BIOINFORMATICS
Website of the academic structure http://datascience.scienze.unipd.it/2017/laurea_magistrale
Department of reference Department of Mathematics
Mandatory attendance No
Language of instruction English
Campus PADOVA

Lecturers
Teacher in charge SILVIO TOSATTO BIO/10
Other lecturers TITO CALI' BIO/10

Mutuating
Course unit code Course unit name Teacher in charge Degree course code
SCP7079278 STRUCTURAL BIOINFORMATICS SILVIO TOSATTO SC1176

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines BIO/10 Biochemistry 6.0

Mode of delivery (when and how)
Period Second semester
Year 1st Year
Teaching methods frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours Individual
study
Shifts
Practice 2.0 16 34.0 No turn
Lecture 4.0 32 68.0 No turn

Calendar
Start of activities 26/02/2018
End of activities 01/06/2018

Examination board
Examination board not defined

Syllabus
Prerequisites: Basic knowledge of optimization methods and machine learning. C++ and/or Java programming languages.
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
1.2) Weak interactions and energy
1.3) Structure and function of DNA and proteins
1.4) Lipids, membranes and cellular transport

2) Computational Biochemistry (4 credits):
2.1) Biological Databases
2.2) Software libraries and concepts for sequence alignments, profiles and database searches
2.3) Sequence - structure - function relationship in proteins and classification
2.4) Methods for the prediction of protein structure from sequence. The CASP experiment.
2.5) Methods for the prediction of protein function. The CAFA experiment.
2.6) Introduction to network and systems biology.
2.7) Genotype – phenotype correlations. The CAGI experiment.
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) and audio recordings (podcasts), 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
  • S. Pascarella, A. Paiardini, Bioinformatica. --: Zanichelli, 2011. Cerca nel catalogo