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Programme of Course "Bioinformatics"



Type of course unit:

Level of course unit:


2nd semester

Number of credits:


Antinisca Di Marco (antiniscadotdimarcoatunivaqdotit)

1. Course Objectives

The course introduces the bioinformatics by identifying the principal problems and solutions the algorithms can deal with and provide, respectively. Moreover, it provides an overview of the main on-line Data bases on biology data and presents their structures and the services they provide to end users. Finally, an introduction to system biology is given, focusing on computer science formal tools (such as, petri nets) that can be used to model biology phenomena or systems. Introduction to Hidden Markov Models

2. Course Contents and learning outcomes (Dublin Descriptors)

Topics of the course include:

  • 1. Biological concepts. Biological databases of metabolic pathways.
  • 2. Biological databases of genes, polimorfisms, mutations and microrna.
  • 3. Alignment algorithms and substitution matrices.
  • 4. Pattern search, phylogenetic trees. Genome wide character association.
  • 5. Computational models for System Biology.
  • 6. Application in several domains (e.g., oncology)

On successful completion of this course, the student should

  • Demonstrate detailed knowledge of: i) alignment algorithms and of the phylogenetic analysis; ii) the functioning and regulation of prokaryotic and eukaryotic cells; iii) on-line data base of genes, microrna, relationships among them, pathways; iv) computational modeling for simple biological systems represented as pathways.

  • Use and organize databases of genomics, proteomics and metabolomics data; Be able to apply phylogenetic analysis to simple genomics data. Use of API of on-line Data Base to interact wiht them and extract data. Use of Petri Nets to model biological pathways.

  • Be able to: i) evaluate and interpret ¬†current literature in areas of bioinformatic practice for analysis of DNA sequence.¬† ii) obtain quantitative results from computational methods. iii) to interpret quantitative results from computational methods.
  • Be able to report on the bioinformatics experiments and studies conducted on DNA sequences and pathways. Have the capacity to discuss the theoretical basics of DNA sequence analysis.

  • Demonstrate capacity to select programs for problem solving and write programs

3. Course Prerequisites

Basic knowledge of imperative and object-oriented programming techniques.

4. Teaching methods and language

The course will be composed by around 40 hours of theory and 8 hours of laboratory and/or advanced seminars during which the theoretical concepts are showed on concrete examples. 


Reference textbooks

  • Volker Sperschneider, Bioinformatics.Problem Solving Paradigms . Springer.
  • selected scientific pubblications.
  • Teacher Notes.
  • Tutorial of on-line data base.

5. Assessment Methods

Project and oral exam. Mid-term exam

Course information last updated on: 18 giugno 2018, 16:10