Course Details for A.Y. 2019/2020

The information on this page refer to the academic year 2019/2020. Therefore, several links are not available and data may be incomplete. To read the current information on the course, if it is still available, go to the university course catalogue . To read information relating other academic years, use the list at the bottom of this page.

A. Year:

2019/2020

Name:

Bioinformatica / Bioinformatics

Type:

Course

Basic information

Code:

DS9001

Sector:

INF/01

Credits:

: Master Degree in Computer Science 6 CFU (b)

Term:

2^nd semester

Degree(s):

Master Degree in Computer Science curriculum GSEEM Elective
Master Degree in Computer Science curriculum NEDAS Elective
Master Degree in Computer Science curriculum SEAS Elective
Master Degree in Computer Science curriculum UBIDIS Elective

Language:

English

Teacher(s):

Antinisca Di Marco

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

Course Content

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)

Learning Outcomes (Dublin Descriptors)

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

Prerequisites and Learning Activities

Basic knowledge of imperative and object-oriented programming techniques.

Assessment Methods and Criteria

Project and oral exam. Mid-term exam

Textbooks

Volker Sperschneider, Bioinformatics.Problem Solving Paradigms , Springer. (punti 3,4 del sillabo)
selected scientific pubblications
Teacher Notes
Tutorial of on-line data base

Internet Resources

Homepage:

http://www.di.univaq.it/adimarco/bioINFO17.html

Course page updates

This course page is available (with possible updates) also for the following academic years:

To read the current information on this course, if it is still available, go to the university course catalogue .

Course information last updated on: 16 gennaio 2019, 13:25