Genomica informazionale: contenuto informativo dei genomi e s divergenza dalla randomicità (2020/2021)

Learning outcomes

Notions of computational genomics linked to information theory will be given.
In particular, the notion of distribution will be a key feature for representing genomes and for analysing their informational content.

Introduction to the course. Basic notions. Genomes as DNA strings. (1 hour)
Distributions. Statistical indexes and Chebyshev inequality. Distribution distances. (2 hours)
Information and information sources. From physical to informational Entropy. (2 hours)
Entropy and mutual entropy. Entropy Circular Principle. Entropic divergence. (2 hours)
Genomes as information sources. Genomic distributions. (2 hours)
Informational genomic indexes. Relations among informational indexes. (2 hours)
Random genomes. Random log normality principle. Logarithmic bounds of randomness (2 hours)

A presentation regarding a scientific article which arguments are similar to those of the course and that has been chosen in agreement with the teacher.