Mathematical modelling of p53 signalling during DNA damage response: a survey

No gene has garnered more interest than p53 since its discovery over 40 years ago. In the last two decades, thanks to seminal work from Uri Alon and Ghalit Lahav, p53 has defined a truly synergistic topic in the field of mathematical biology, with a rich body of research connecting mathematic endeavour with experimental design and data. In this review we survey and distill the extensive literature of mathematical models of p53. Specifically, we focus on models which seek to reproduce the oscillatory dynamics of p53 in response to DNA damage. We review the standard modelling approaches used in the field categorising them into three types: time delay models, spatial models and coupled negative-positive feedback models, providing sample model equations and simulation results which show clear oscillatory dynamics. We discuss the interplay between mathematics and biology and show how one informs the other; the deep connections between the two disciplines has helped to develop our understanding of this complex gene and paint a picture of its dynamical response. Although yet more is to be elucidated, we offer the current state-of-the-art understanding of p53 response to DNA damage

Stress-controlled hysteresis and long-time dynamics of implicit differential equations arising in hypoplasticity

summary:A long-time dynamic for granular materials arising in the hypoplastic theory of Kolymbas type is investigated. It is assumed that the granular hardness allows exponential degradation, which leads to the densification of material states. The governing system for a rate-independent strain under stress control is described by implicit differential equations. Its analytical solution for arbitrary inhomogeneous coefficients is constructed in closed form. Under cyclic loading by periodic pressure, finite ratcheting for the void ratio is derived in explicit form, which converges to a limiting periodic process (attractor) when the number of cycles tends to infinity

Approximate Polynomial Greatest Common Divisor

Title: Approximate Polynomial Greatest Common Divisor Author: Ján Eliaš Department: Department of Numerical Mathematics, MFF UK Supervisor: Doc. RNDr. Jan Zítko, CSc., Department of Numerical Mathematics, MFF UK Abstract: The computation of polynomial greatest common divisor (GCD) ranks among basic algebraic problems with many applications. The Euclidean algorithm is the oldest and usual technique for computing GCD. However, the GCD computation problem is ill-posed, particularly when some unknown noise is applied to the polyno- mial coefficients. Since the Euclidean algorithm is unstable, new methods have been extensively studied in recent years. Methods based on the numerical rank estimation represent one group of current meth- ods. Their disadvantage is that the numerical rank cannot be computed reliably due to the sensitivity of singular values on noise. The aim of the work is to overcome the ill-posed sensitivity of GCD computation in the presence of noise. Keywords: AGCD, Sylvester matrix, numerical rank, TL

Přibližný polynomiální největší společný dělitel

Název práce: Approximate Polynomial Greatest Common Divisor Autor: Ján Eliaš Katedra: Katedra numerické matematiky, MFF UK Vedoucí diplomové práce: Doc. RNDr. Jan Zítko, CSc., Katedra numerické matematiky, MFF UK Abstrakt: Výpočet najväčšieho spoločného delitel'a (GCD) dvoch polynómov patrí medzi základné problémy numerickej matematiky. Euklidov algoritmus je najstaršia a bežne používaná metóda na výpočet GCD, avšak táto metóda je značne nestabilná. Výpočet GCD je navyše zle postavená úloha v tom zmysle, že l'ubovol'ný šum pridaný ku koeficientom polynómov redukuje netriviálny GCD na konštantu. Jednu skupinu nových metód predstavujú metódy založené na odhade numerickej hod- nosti matíc. Operácie s polynómami sa tak redukujú na maticové počty. Ich nevýhodou je, že ani numerická hodnost' nemusí byt' spočítaná presne a hodnoverne kvôli citlivosti singulárnych čísel na šume. Ciel'om práce je prekonat' citlivost' výpočtu GCD na šume. Klíčová slova: AGCD, Sylvesterova matica, numerická hodnost', TLSTitle: Approximate Polynomial Greatest Common Divisor Author: Ján Eliaš Department: Department of Numerical Mathematics, MFF UK Supervisor: Doc. RNDr. Jan Zítko, CSc., Department of Numerical Mathematics, MFF UK Abstract: The computation of polynomial greatest common divisor (GCD) ranks among basic algebraic problems with many applications. The Euclidean algorithm is the oldest and usual technique for computing GCD. However, the GCD computation problem is ill-posed, particularly when some unknown noise is applied to the polyno- mial coefficients. Since the Euclidean algorithm is unstable, new methods have been extensively studied in recent years. Methods based on the numerical rank estimation represent one group of current meth- ods. Their disadvantage is that the numerical rank cannot be computed reliably due to the sensitivity of singular values on noise. The aim of the work is to overcome the ill-posed sensitivity of GCD computation in the presence of noise. Keywords: AGCD, Sylvester matrix, numerical rank, TLSDepartment of Numerical MathematicsKatedra numerické matematikyFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult

Problémy spojené s výpočtem největšího společného dělitele

Department of Numerical MathematicsKatedra numerické matematikyFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult

Calculation of the greatest common divisor of perturbed polynomials

summary:The coefficients of the greatest common divisor of two polynomials $f$ and $g$ (GCD$(f,g)$) can be obtained from the Sylvester subresultant matrix $S_j(f,g)$ transformed to lower triangular form, where $1 \leq j \leq d$ and $d =$ deg(GCD$(f,g)$) needs to be computed. Firstly, it is supposed that the coefficients of polynomials are given exactly. Transformations of $S_j(f,g)$ for an arbitrary allowable $j$ are in details described and an algorithm for the calculation of the GCD$(f,g)$ is formulated. If inexact polynomials are given, then an approximate greatest common divisor (AGCD) is introduced. The considered techniques for an AGCD computations are shortly discussed and numerically compared in the presented paper

Approximate polynomial GCD

summary:The computation of polynomial greatest common divisor (GCD) ranks among basic algebraic problems with many applications, for example, in image processing and control theory. The problem of the GCD computing of two exact polynomials is well defined and can be solved symbolically, for example, by the oldest and commonly used Euclid’s algorithm. However, this is an ill-posed problem, particularly when some unknown noise is applied to the polynomial coefficients. Hence, new methods for the GCD computation have been extensively studied in recent years. The aim is to overcome the ill-posed sensitivity of the GCD computation in the presence of noise. We show that this can be successively done through a TLS formulation of the solved problem, [1,5,7]