Biostatistics and bioinformatics

A.Y. 2019/2020
Overall hours
Learning objectives
This module teaches the basic principles and practices of the main computational and statistical methods necessary to analyze the "omics" data that current technologies make available.
Expected learning outcomes
At the end of the course, students will be able to examine the genomic information generated by recent molecular biology techniques (eg NGS and microarray).
The students involved the knowledge of IT and statistical tools for the management of genomic data with particular regard to sequencing techniques and all those methods aimed at analyzing, understanding genomic data and animal genetic variability. The course therefore intends to provide students with knowledge of mathematical / statistical and IT tools from the pre-processing of the raw data, to their analysis and their biological interpretation.
Course syllabus and organization

Unique edition

Lesson period
Second semester
Course syllabus
Computer exercises with R (32 hours): Introduction to the R language, Graphic representations with R, I / O functions, Flow control, Processing and structuring of information. Case studies on analysis of animal gene expression profiles. Examples of bioinformatics tools available: the main software available as web applications and open source programs
Prerequisites for admission
Specific preliminary knowledge is not required to attend the course.
Teaching methods
The form of teaching involves lectures, tutorials and practical sessions.
The powerpoint presentations will be available on Ariel platform.
Tutorials and books:
1. Discovering statistics using IBM SPSS statistics. A Field. sage, 2013
2. Korpelainen, Eija, et al. RNA-seq data analysis: a practical approach. Chapman and Hall/CRC, 2014.
Assessement methods and criteria
The exam will be divided into two parts: a practical test and if the test is successful, an oral test based on verifying understanding and reworking of the contents of the program carried out in class.
The final grade will take into account the communicative ability and the ability to adequately motivate statements, analyzes and judgments during the interview.
Practicals: 32 hours
Lessons: 32 hours
Professor: Cava Claudia
Educational website(s)