Corso di Laurea in Biotecnologie

BIOLOGIA COMPUTAZIONALE

Computational Biology

Anno accademico 2013/2014

Sommario insegnamento

• Obiettivi formativi
• Risultati dell'apprendimento attesi
• Programma
• Testi consigliati e bibliografia
• Strumenti didattici

Obiettivi formativi

The course aims at familiarizing the students with the most important computational tools used in the study of gene expression and gene regulation. Gene expression data are investigated using statistical techniques for class comparison, including multiple testing correction; class discovery: clustering algorithms and functional characterization; and survival analysis for cancer gene expression datasets. Gene regulation is studied using both regulatory sequence analysis tools and high-throughput experimental datasets of regulatory relevance provided by the Encode project.

Risultati dell'apprendimento attesi

Upion completion of the course the students are expected to be able to:

- understand the main concepts underlying the analysis of gene expression and gene regulation data

- perform basic analysis of gene expression datasets, including both class comparison and class discovery, using online tools

- visualize chip-seq data on the UCSC genome browser, perform basic maniuplation of .bed files and simple comparisons with results of gene expression experiments

Programma

1. Computational analysis of gene expression: class comparison

2. Computational analysis of gene expression: class discovery

3. Use of repositories of gene expression data such as GEO

4. Interpretation and visualization of Chip-seq dataset

5. Basic manipulation of .bed files; integration of Chip-seq and transcriptomic data

Slides and journal articles will be provided

• Materiale didattico
• Bacheca appelli
• Vai a Moodle
• Visita i forum