Search results for "modelling"

The Poly-ADP-Ribose Polymerase PARP Modulates the Activity of the Nucleosome Remodeling ATPase ISWI

2008

Through Predictive Personalized Medicine.

2020

Neuroblastoma (NBM) is a deadly form of solid tumor mostly observed in the pediatric age. Although survival rates largely differ depending on host factors and tumor-related features, treatment for clinically aggressive forms of NBM remains challenging. Scientific advances are paving the way to improved and safer therapeutic protocols, and immunotherapy is quickly rising as a promising treatment that is potentially safer and complementary to traditionally adopted surgical procedures, chemotherapy and radiotherapy. Improving therapeutic outcomes requires new approaches to be explored and validated. In-silico predictive models based on analysis of a plethora of data have been proposed by Lomba…

Pharmacophore modelling as useful tool in the lead compounds identification and optimization

2012

The goal of computer-aided molecular design methods in modern medicinal chemistry is to reduce the overall cost and time associated to the discovery and development of a new drug by identifying the most promising candidates to focus the experimental efforts on. Very often, many drug discovery projects have reached already a well-advanced stage before detailed structural data on the protein target have become available. A possible consequence is that often, medicinal chemists develop novel compounds for a target using preliminary structure–activity information, together with the theoretical models of interactions. Only responses that are consistent with the working hypothesis contribute to a…

Frequency-specific network activity predicts bradykinesia severity in Parkinson’s disease

2021

Highlights • Parallel subnetworks are affected in bradykinesia. • The primary motor and the premotor cortex are common nodes with task-specificity. • Beta activity decreases, gamma activity increases with improvement of bradykinesia. • Subthalamic stimulation reduces beta, increases gamma power in ipsilateral cortex. • Subnetworks act with frequency-specific oscillations.

On universality of critical behavior in the focusing nonlinear Schrödinger equation, elliptic umbilic catastrophe and the Tritronquée solution to the…

2008

We argue that the critical behavior near the point of “gradient catastrophe” of the solution to the Cauchy problem for the focusing nonlinear Schrodinger equation \(i\epsilon \varPsi _{t}+\frac{\epsilon^{2}}{2}\varPsi _{xx}+|\varPsi |^{2}\varPsi =0\) , e ≪1, with analytic initial data of the form \(\varPsi (x,0;\epsilon)=A(x)e^{\frac{i}{\epsilon}S(x)}\) is approximately described by a particular solution to the Painleve-I equation.

Hygro-elasto-plastic model for planar orthotropic material

2015

An in-plane elasto-plastic material model and a hygroexpansivity-shrinkage model for paper and board are introduced in this paper. The input parameters for both models are fiber orientation anisotropy and dry solids content. These two models, based on experimental results, could be used in an analytical approach to estimate, for example, plastic strain and shrinkage in simple one-dimensional cases, but for studies of the combined and more complicated effects of hygro-elasto-plastic behavior, a numerical finite element model was constructed. The finite element approach also offered possibilities for studying different structural variations of an orthotropic sheet as well as buckling behavior…

Comparing equilibration schemes of high-molecular-weight polymer melts with topological indicators.

2021

Abstract Recent theoretical studies have demonstrated that the behaviour of molecular knots is a sensitive indicator of polymer structure. Here, we use knots to verify the ability of two state-of-the-art algorithms—configuration assembly and hierarchical backmapping—to equilibrate high-molecular-weight (MW) polymer melts. Specifically, we consider melts with MWs equivalent to several tens of entanglement lengths and various chain flexibilities, generated with both strategies. We compare their unknotting probability, unknotting length, knot spectra, and knot length distributions. The excellent agreement between the two independent methods with respect to knotting properties provides an addit…

Non-crossing parametric quantile functions: an application to extreme temperatures

2019

Quantile regression can be used to obtain a non-parametric estimate of a conditional quantile function. The presence of quantile crossing, however, leads to an invalid distribution of the response and makes it difficult to use the fitted model for prediction. In this work, we show that crossing can be alleviated by modelling the quantile function parametrically. We then describe an algorithm for constrained optimisation that can be used to estimate parametric quantile functions with the noncrossing property. We investigate climate change by modelling the long-term trends of extreme temperatures in the Arctic Circle.

Treed Gaussian Process Regression for Solving Offline Data-Driven Continuous Multiobjective Optimization Problems

2023

Abstract For offline data-driven multiobjective optimization problems (MOPs), no new data is available during the optimization process. Approximation models (or surrogates) are first built using the provided offline data and an optimizer, e.g. a multiobjective evolutionary algorithm, can then be utilized to find Pareto optimal solutions to the problem with surrogates as objective functions. In contrast to online data-driven MOPs, these surrogates cannot be updated with new data and, hence, the approximation accuracy cannot be improved by considering new data during the optimization process. Gaussian process regression (GPR) models are widely used as surrogates because of their ability to pr…

Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latencies

2018

We consider multiobjective optimization problems where objective functions have different (or heterogeneous) evaluation times or latencies. This is of great relevance for (computationally) expensive multiobjective optimization as there is no reason to assume that all objective functions should take an equal amount of time to be evaluated (particularly when objectives are evaluated separately). To cope with such problems, we propose a variation of the Kriging-assisted reference vector guided evolutionary algorithm (K-RVEA) called heterogeneous K-RVEA (short HK-RVEA). This algorithm is a merger of two main concepts designed to account for different latencies: A single-objective evolutionary a…