Acquisition of methods of discrete mathematics in the analysis of biological phenomena, with a major emphasis on the computational analysis of genomes. In particular discrete probability and information theory are revisited in the perspective of genome analysis.
Basic notation on sequences and strings. The problems of substring and superstring. Lexicographic ordering and suffix arrays. Advanced combinatorial schemata and discrete probability. Random sequences and fundamental probability laws on them (Bernoulli, Poisson, Exponential, Gauss). Information sources and entropy. Conditional entropy, entropic divergences and mutual information. Genomes, genomic indexes, genomic dictionaries, genomic distributions and entropies. Representations and visualizations of genomes. Types of codes and genetic code. Sequence duplications and double sequences. The sequence paradox and other life paradoxes. Cellular dynamics and recurrent equations. Biological networks and their principal aspects.
Oral exam, with a possible project.
- Manca V. - Topics in discrete mathematics (Notes freely distributed at the beginning of the course, 130 pages, 2017)
- Bonnici V, Manca V - Informational laws of genome structures. Scientific Report, Volume 6, Article number 28840 doi 10.1038/srep28840, Nature Publishing Group (2016)
- Manca V. - The principles of informational genomics. Theoretical Computer Science (C), doi 10.1016/j.tcs.2017.02.0352017. Elsevier B. V. (2017)
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