BIOCHEMISTRY- (60 hours )
Structure and functions of biomolecules (proteins, nucleic
Enzymes and catalysis
Protein and nucleotide metabolism
Biochemical mechanisms related with cellular growth and
MOLECULAR BIOLOGY (50 hours)
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 BIOLOGY (20 hours)
Homotypic and heterotypic cell-cell interactions.
GENETICS (40 hours)
Transmission of genetic inheritance
Modification of gene expression in mouse.
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
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
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
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.