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Programme of Course "Bioinformatica"

Code:

DS9001

Type of course unit:

Bachelor Degree in Computer Science curriculum General: Elective
Master Degree in Computer Science curriculum General: Elective

Level of course unit:

Undergraduate Degrees
Postgraduate Degrees

Semester:

2nd semester

Number of credits:

Master Degree in Computer Science: 6 (workload 150 hours)

Teachers:

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. 

2. Course Contents and learning outcomes (Dublin Descriptors)

Topics of the course include:

  • 1. Biological databases of genes, polimorfisms e mutations.
  • 2. Biological databases of metabolic pathways.
  • 3. Alignment algorithms and substitution matrices.
  • 4. Pattern search, phylogenetic trees. Genome wide character association.
  • 5. Computational models for System Biology.
  • 6. BioPhyton

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) Phyton language and BioPhyton libraries; 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 BioPhyton libraries for bioinformatics aims. 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 20 hours of (computer science!) laboratory during which the theoretical concepts are showed on concrete examples. 

Language:Italian[info]

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: 31 ottobre 2014, 15:02