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Subject: BIOINFORMATION TECHNOLOGY (A.A. 2023/2024)

master degree course in COMPUTER SCIENCE

Course year 1
CFU 6
Teaching units Unit Bioinformatica
Related or Additional Studies (lesson)
  • TAF: Supplementary compulsory subjects SSD: ING-IND/34 CFU: 6
Teachers: Andrea BIGHINATI
Exam type oral
Evaluation final vote
Teaching language Italiano
Contents download pdf download

Teachers

Andrea BIGHINATI

Overview

The course aims at providing the knowledge and skills necessary for the computational analysis of data related to biological macromolecules. These activities are preparatory to deepen in more specialized and professionalizing biological disciplinary sectors. The class also introduces students to the application of algorithms and IT tools essential to analyze and understand the quantitative aspects related to macromolecules.

Admission requirements

The class requires basic knowledge of Mathematics, Computer Science and Statistics applied to biology, organic chemistry, cell biology, biochemistry, molecular biology, genetics.

Course contents

La scansione dei contenuti per CFU è da intendere come puramente indicativa. Essa può infatti subire modifiche nel corso dell’insegnamento alla luce dei feedback degli studenti e delle studentesse

1 CFU (8 ore):
- Introduzione alla Bioinformatica
- Le banche dati biologiche e la loro struttura
- Concetti e principi per l'analisi delle sequenze (stringhe ed algoritmi)

2 CFU (16 ore):
- Allineamento di sequenze: definizioni e significato biologico
- Allineamento ottimo: globale o locale
- BLAST e allineamenti euristici

2 CFU (16 ore):
- Ricostruzione ed annotazione di un genoma
- Annotazioni ab-initio
- RNA-seq OLC (Overlap-Layout-Consensus)
- Analisi di trascrittomica
- UCSC Genome Browser

1 CFU (8 ore):
- Database di proteine
- Descrittori di elementi funzionali in sequenze proteiche
- Profili di sequenza
- Proteins network

Teaching methods

Teaching is given through face-to-face lectures (theory and application examples) which are carried out with the aid of audiovisual media (Power Point presentations) and practical exercises in the use of computational tools. Attendance to face-to-face lectures (theory, application examples and exercises) is not compulsory. The course language is Italian.

Assessment methods

The exam will take place at the end of the course according to the official exam schedule. The test is oral. The duration of the interview is about 15 minutes during which the student is asked to illustrate two topics related to sequence alignment and genome analysis. The interview is aimed at evaluating: - knowledge and understanding skills; - the application of knowledge and understanding; - autonomy of judgment. The evaluation parameters consist of: - the application of knowledge and understanding (80%); - autonomy of judgment (15%); - communication skills (5%). The final grade of the exam will be communicated at the end of the interview; the verbalization will take place through Esse3.

Learning outcomes

1) Knowledge and understanding
at the end of the course, it is hoped that the student will be able to:
a) apply mathematical, statistical and computer methods to the analysis of the sequences of biological macromolecules;
b) use computational methods of genomic and post-genomic analysis.
2) Ability to apply
a) logical-mathematical, statistical, computer and physical tools;
b) bioinformatics knowledge;
c) methods for consulting national and international documents on bioethical aspects, bibliographic material, databases.
3) Autonomy of judgment
a) plan and interpret data for laboratory testing and safety;
b) reorganize the knowledge learned and implement one's own capacity for critical and autonomous evaluation of what has been learned.
4) Communication skills
a) express their knowledge correctly and logically, recognizing the required topic and responding in a timely and complete manner to the exam questions.
b) communicate in Italian and foreign (English) written and / or oral with appropriate scientific language.
5) Learning skills
a) develop autonomy in study and laboratory work;
b) know how to consult bibliographic material and databases and other resources of the network;
c) to learn basic cognitive tools for the continuous updating of knowledge.

Readings

Un testo a scelta fra:
- M. Helmer Citterich, F. Ferre’, G. Pavesi, G. Pesole, C. Romualdi Fondamenti di bioinformatica, Zanichelli, 2018
- J. Pevsner, Bioinformatics and functional genomics, Wiley-Blackwell, 2009
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