UniversitÓ degli Studi di Torino

 First Year Classes

BIOCHEMISTRY- (60 hours ) 
Structure and functions of biomolecules (proteins, nucleic acids)
Enzymes and catalysis
Energetic metabolism
Protein and nucleotide metabolism
Protein processing
Biochemical mechanisms related with cellular growth and differentiation.

Regulation of transcription
Regulation of translation
Control of gene expression
Protein-protein protein-nucleic acid interactions, 
Mechanisms of DNA duplication
Mechanisms of DNA repair.

Cellular Compartimentalization
Molecule trafficking 
Cell differentiation
Embryo development
Cell motility
Homotypic and heterotypic cell-cell interactions.

GENETICS (40 hours)
Chromosomal genetics 
Human genetics
Transmission of genetic inheritance
Gene therapy
Modification of gene expression in mouse. 

Students without an ungradutated biological experience have to attend Laboratory training.

Complements of Advanced Calculus and Function Theory
Complex analytic functions, linear differential equations, Laplace, Fourier and other integral transforms. Finite and infinite dimensional vector spaces. Elements of Hilbert space theory. Special functions. Introduction to the use of symbolic manipulation computer programmes such as MATHEMATICA, MAPLE and MATHLAB. Practical exercises on: <<doing mathematics on a computer>>.

Group Theory
Discrete groups, crystallographic groups, symmetric group of permutations. Representations and characters. Lie groups and Lie algebras. Conformal transformations and applications to image processing. Applications to the resolution of analytic problems with special functions. Introduction to differential geometry, homogeneous spaces and their applications in statistical physics. Practical exercises with symbolic manipulation programmes: <<doing mathematics on a computer>>.

Probability theory and basic Statistical Mechanics.
This is the core of the educational programme from the point view of its physical mathematical basis.Elementary probability theory and limit theorems: Binomial, Poisson and Gaussian distributions.Random walks and Markov chains. Equilibrium statistical mechanics: entropy and probability, microcanonical, canonical and grancanonical ensembles.

Statistical Field Theory
Statistical field theory. Critical phenomena, universality and scaling. Mean field approximation

Basic introduction to methods of computer science and their applications in biology.
Basic notions on computer operative systems. Introduction to object oriented programming and to basic computer languages, C/C++ and Perl.

Applied computational methods.
Algorithms for the analysis and comparison of nucleotide sequences. Markovian chains, Smith-Lanterman algorithms. Combinatorial Optimization Analysis for  Protein folding. Simulated Annealing, network theory, cluster reconstruction and pattern recognition. Data mining.




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