Modelli di calcolo naturale (2012/2013)
The course intends to present an algorithmic and computational analysis of biological phenomena with a major emphasis on the genomic representation of information and on the analysis of basic biological dynamics.
Protocells and informational structures. Eigen's paradox, and enzymatic paradox. Essentials on grammars, automata, patterns, formal languages, and information theory (entropy, codes, and compression). Multisets and chemical reactions. Polymers and sequences. Multisets and membranes. Mathematical structure of DNA and double helix. DNA operations on double strings. DNA test-tube operations and fundamental protocols. DNA computing. PCR e XPCR protocols. Genome analysis based on dictionaries. Genomic indexes and genome representations. Metabolic systems and discrete representation of biochemical systems. Membrane systems and MP systems. Metabolic fluxes, regulation maps and reaction maps. Examples of MP models. MP grammars and approximations of real functions. Inverse dynamics. Least square estimation and statistical regression for MP systems. LGSS (Log Gain Stoichiometric Stepwise regression) algorithm. MetaPLab software and examples of computational metabolic experiments. Basic regulative mechanisms in biological phenomena. Metabolism and replication. Metabolic ubiquity. Biomedical applications of MP theory.
Oral examination with a possible project.
Data from AA 2012/2013 are not available yet