Methods in bioinformatics

A.A. 2016/2017
Insegnamento per
Crediti massimi
Ore totali
Obiettivi formativi
The lectures deal with computational methods and techniques for Computationl Biology and Bioinformatics, covering both programming languages for Bioinformatics and Machine Learning Methods for Computational Biology.

At the end of the course the student should acquire:
- Basic knowledge of machine learning algorithms
- Ability to apply Machine Learning algorithms to the analysis of complex biomolecular data
- Programming skills to realize software applications in bioinformatics.

Struttura insegnamento e programma

Edizione attiva
Lezioni: 48 ore
1. The R programming language.
- Main data structures in R: vectors, factors, matrices, arrays, lists and environments.
- Control of execution flow: blocks, conditional statements, loops.
- Functions and scripts
- I/O functions and operators; R data import/export
- R graphics
- Object-oriented programming in R
- Packages and R "extensions"

2. Machine Learning and Computational Biology.
- Learning from data: supervised, unsupervised and semi-supervised machine learning methods.
- Some examples of Computational Biology applications of Machine Learning:
- Automated functional annotation of proteins
- Systems Biology approaches to disease gene prioritization and to the analysis of biological networks.
- Outcome and abnormal phenotype prediction from multiple sources of omics data.
- Prediction of genetic variants and mutations associated with genetic diseases and cancer.
Prerequisiti e modalità di esame
Oral discussion of the contents of the course and/or development/application of a R program to a bioinformatics problem.
Metodi didattici
Lectures and lab exercises, where each student will have a personal computer at his/her disposal.
Materiale didattico e bibliografia
Slides, notes and scientific papers will be available from the course web site:
Primo semestre
Primo semestre
Modalità di valutazione
Giudizio di valutazione
voto verbalizzato in trentesimi
Siti didattici
Per appuntamento tramite e-mail
stanza 3011, III piano - Dipartimento di Informatica, via Celoria 18