#ABOUT Year 2 in L'Aquila;

Cancer Modelling and Simulation

The specialization track “Cancer Modelling and Simulation” will be given at the Department of Information Engineering, Computer Science and Mathematics of UAQ in collaboration with the Department of Biotechnological and Applied Clinical Sciences at the same University. The proposed track addresses modelling and simulation of cancer genetics, evolution, and treatment using continuum bio-fluid dynamic modelling, fluid-solid interaction modelling, reaction-diffusion modelling, systems biology and control theory.

The group at L’Aquila features an important research stream on these subjects, see the contribution by M. Di Francesco in the mathematical theory of chemotaxis modelling and biological aggregation phenomena, as well as the results obtained by D. Donatelli in mathematical fluid dynamics and biofluid dynamics and cancer modelling and simulation.

The course “Advanced analysis” (taught by C. Lattanzio) provides advanced modelling tools proper for mathematical analysis. The course “Mathematical biofluid dynamics” (taught by D. Donatelli) tackles modern fluid-dynamical modelling techniques in cancer modelling, specifically cells-ECM interaction models. “Biomathematics”, taught by C. Pignotti, deals with cell population models and chemotaxis modelling, with applications to cancer modelling. The course “Systems Biology” covers deterministic and stochastic modelling and control of gene transcription networks and enzymatic reactions with application to cancer drug response. The Course “Cancer Genetics and Biology for Mathematical Modelling” is jointly taught by Dr. Alessandra Tessitore and Dr. Daria Capece (formerly at Imperial College, London), who are members of the Department of Biotechnological and Applied Clinical Sciences at UAQ.

Students of this specialization branch will have the opportunity to prepare their MSc thesis in collaboration with the staff from external institutions such as CSCAMM at the University of Maryland, WWU Muenster in Germany, KAUST, University of Oxford, Imperial College London. They may also spend the thesis semester in one of the pharmaceutical companies of the Capitank Consortium carrying out R&D projects on cancer genetics, evolution and treatment.

September 2022

September 2022

September 2023

🎓 Graduation

#Year 2 in L'Aquila EMJMD InterMaths Study Track

Cancer Modelling and Simulation;

Campus

University of L'Aquila

Year

2

Semester

1

ECTS Credits

30

Language

English
Advanced analysis

ECTS Credits: 6    |    Semester: 1    |    Year: 2    |    Campus: University of L'Aquila    |    Language: English

Unit Coordinator: Corrado Lattanzio

Aims:

Knowledge of mathematical methods that are widely used by researchers in the area of Applied Mathematics, as Sobolev Spaces, distributions. Application of this knowledge to a variety of topics, including the basic equations of mathematical physics and some current research topics about linear and nonlinear partial differential equations.

Content:

  • Distributions. Locally integrable functions. The space of test function D(Ω). Distributions associated to locally integrable functions. Singular distributions. Examples. Operations on distributions: sum, products times functions, change of variables, restrictions, tensor product. Differentiation and his properties; comparison with classical derivatives. Differentiation of jump functions. Partition of unity. Support of a distribution; compactly supported distributions.;
  • Convolution. Convolution in Lp spaces. Regularity of the convolution. Regularizing sequences and smoothing by means of convolutions. Convolution between distributions and regularization of distributions. Denseness of D(Ω) in D′(Ω).;
  • Sobolev spaces. Definition of weak derivatives and his motivation. Sobolev spaces Wk,p(Ω) and their properties. Interior and global approximation by smooth functions. Extensions. Traces. Embeddings theorems: Gagliardo–Nirenberg–Sobolev inequality and embedding theorem for p n. Sobolev in- equalities in the general case. Compact embeddings: Rellich–Kondrachov theorem, Poincaré inequalities. Embedding theorem for p = n. Characterization of the dual space H−1.;
  • Second order parabolic equations. Definition of parabolic operator. Weak solutions for linear parabolic equations. Existence of weak solutions: Galerkin approximation, construction of approximating solutions, energy estimates, existence and uniqueness of solutions.;
    First order nonlinear hyperbolic equations. Scalar conservation laws: derivation, examples. Weak solutions, Rankine-Hugoniot conditions, entropy conditions. L1 stability, uniqueness and comparison for weak entropy solutions. Convergence of the vanishing viscosity and existence of the weak, entropy solution. Riemann problem.

Pre-requisites:

Basic notions of functional analysis, functions of complex values, standard properties of classical solutions of semilinear first order equations, heat equation, wave equation, Laplace and Poisson's equations.

Reading list:

H. Brezis, Functional Analysis, Sobolev Spaces and Partial Differential Equations. Universi- text, Springer.;
C.M. Dafermos, Hyperbolic Conservation Laws in Continuum Physics, Springer.;
L.C. Evans, Partial Differential Equations. Graduate Studies in Mathematics, Vol. 19, AMS.;
G. Gilardi, Analisi 3. McGraw–Hill.;
V.S. Vladimirov, Equations of Mathematical Physics. Marcel Dekker, Inc.

Mathematical fluid and biofluid dynamics

ECTS Credits: 6    |    Semester: 1    |    Year: 2    |    Campus: University of L'Aquila    |    Language: English

Unit Coordinator: Donatella Donatelli

Aims:

The aim of the course is to give an overview of fluid dynamics from a mathematical viewpoint, and to introduce students to the mathematical modeling of fluid dynamic type with a particular attention to biofluid dynamics.

At the end of the course students will be able to perform a qualitative and quantitative analysis of solutions for particular fluid dynamics problems and to use concepts and mathematical techniques learned from this course for the analysis of other partial differential equations.

Content:

  • Derivation of the governing equations: Euler and Navier-Stokes
  • Eulerian and Lagrangian description of fluid motion; examples of fluid flows
  • Vorticity equation in 2D and 3D
  • Dimensional analysis: Reynolds number, Mach Number, Frohde number.
  • From compressible to incompressible models
  • Existence of solutions for viscid and inviscid fluids
  • Fluid dynamic modeling in various fields: magnetohydrodynamics, combustion, astrophysics.
  • Modeling for biofluids: hemodynamics, cerebrospinal fluids, cancer modelling, animal locomotion, bioconvection for swimming microorganisms.

Pre-requisites:

Basic notions of functional analysis and multi variable calculus, standard properties of the heat equation, wave equation, Laplace and Poisson's equations.

#Final Semester Dissertation;

The thesis topic can be proposed by the track coordinator or by the student. In any case, the local coordinator has the responsibility to provide an advisor. The student’s taste and expectations are met whenever possible. The student must write a short thesis project, with the help of her/his advisor, to be submitted to the Executive Committee, which has to approve the thesis project before its formal start. The thesis topic will preferably deal with a problem proposed by a private company, if possible chosen among the Consortium Industrial Partners.

The final master’s degree examination, while respecting the local regulations, will consist as a general rule in two parts: an oral examination on the topic of the thesis, and the defense of the thesis.

In this examination the candidate will be required to demonstrate good knowledge of his/her specialization track and a capability for working independently and solving problems on experimental, numerical, technological, design or modelling applications. The semester may include an internship within a collaborating company or institution. In this case, a tutor from the involved partner and an academic supervisor will be appointed.

Students who have satisfied all the requirements of the degree programme will be awarded a Joint Master Degree in Interdisciplinary Mathematics by the Universities where the student has spent at least one semester

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