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Nanoparticles functionalized with multiple ligands can be programmed to bind biological targets depending on the receptors they express, providing a general mechanism exploited in various technologies, from selective drug-delivery to…

Chemical Physics · Physics 2017-02-22 Stefano Angioletti-Uberti

Determination of binding affinity of proteins in the formation of protein complexes requires sophisticated, expensive and time-consuming experimentation which can be replaced with computational methods. Most computational prediction…

Quantitative Methods · Quantitative Biology 2020-12-14 Wajid Arshad Abbasi , Fahad Ul Hassan , Adiba Yaseen , Fayyaz Ul Amir Afsar Minhas

We consider the behaviour of a critical system in the presence of a gradient perturbation of the couplings. In the direction of the gradient an interface region separates the ordered phase from the disordered one. We develop a scaling…

Other Condensed Matter · Physics 2009-10-06 Thierry Platini , Dragi Karevski , Loïc Turban

Current experimental and theoretical studies on the effect of intermolecular interactions on molecular conduction appear to be in conflict with each other. In particular, some experimental results, e.g., the observation of 2-dimensional…

Mesoscale and Nanoscale Physics · Physics 2007-07-23 A. Landau , L. Kronik , A. Nitzan

Binding of a ligand on a protein changes the flexibility of certain parts of the protein, which directly affects its function. These changes are not the same at each point, some parts become more flexible and some others become stiffer.…

Biomolecules · Quantitative Biology 2015-01-13 Burak Erman

For solving the longstanding materials science problem of correlating elastic properties of a solid material to the formation of cracks we present a new general concept. This concept is applied to the technologically most important cracks…

Materials Science · Physics 2007-05-23 Petr Lazar , Raimund Podloucky , Walter Wolf

The growing correlation length observed in supercooled liquids as their temperature is lowered has been studied with the aid of a single occupancy cell model. This model becomes more accurate as the density of the system is increased. One…

Statistical Mechanics · Physics 2013-04-17 Christopher J. Fullerton , M. A. Moore

Among the Renormalization Group Theory scaling rules relating critical exponents, there are hyperscaling rules involving the dimension of the system. It is well known that in Ising models hyperscaling breaks down above the upper critical…

Disordered Systems and Neural Networks · Physics 2018-01-24 P. H. Lundow , I. A. Campbell

We study the problem of learning the structure and parameters of the Ising model, a fundamental model of high-dimensional data, when observing the evolution of an associated Markov chain. A recent line of work has studied the natural…

Machine Learning · Computer Science 2025-07-22 Jason Gaitonde , Ankur Moitra , Elchanan Mossel

We devise a method for predicting certain receptor-ligand binding behaviors, based on stochastic dynamical modelling. We consider the dynamics of a receptor binding to a ligand on the cell membrane, where the receptor and ligand perform…

Molecular Networks · Quantitative Biology 2023-02-17 Xi Chen , Hui Wang , Jinqiao Duan

In a previous paper, we examined a class of possible conformations for helically patterned filaments in contact with a bonding surface. In particular, we investigated geometries where contact between the pattern and the surface was improved…

Subcellular Processes · Quantitative Biology 2016-12-12 Nash Rochman , Sean X. Sun

The identification of microscopic models describing the low-energy properties of correlated materials has been a central goal of spectroscopic measurements. We demonstrate how 2D non-linear spectroscopy can be used to distinguish effective…

Strongly Correlated Electrons · Physics 2023-12-12 GiBaik Sim , Frank Pollmann , Johannes Knolle

We analyze the phenomenon of stochastic resonance in an Ising-like system on a small-world network. The system, which is subject to the combined action of noise and an external modulation, can be interpreted as a stylized model of opinion…

Disordered Systems and Neural Networks · Physics 2009-11-07 Marcelo Kuperman , Damian Zanette

We study the two-dimensional Ising model on a network with a novel type of quenched topological (connectivity) disorder. We construct random lattices of constant coordination number and perform large scale Monte Carlo simulations in order…

Statistical Mechanics · Physics 2018-03-07 Manuel Schrauth , Julian A. J. Richter , Jefferson S. E. Portela

We study the statistical properties of Ising spin chains with finite (although arbitrary large) range of interaction between the elements. We examine mesoscopic subsystems (fragments of an Ising chain) with the lengths comparable with the…

Statistical Mechanics · Physics 2009-11-13 S. S. Apostolov , Z. A. Mayzelis , O. V. Usatenko , V. A. Yampol'skii

Fibrous networks are ideal functional materials since they provide mechanical rigidity at low weight. Such structures are omnipresent in natural biomaterials from cells to tissues, as well as in man-made materials from polymeric composites…

We compute numerically the second and third order nonlinear magnetic susceptibilities of an Ising ladder model in the context of two-dimensional coherent spectroscopy by using the infinite time-evolving block decimation method. The Ising…

Strongly Correlated Electrons · Physics 2023-04-26 Qi Gao , Yang Liu , Haijun Liao , Yuan Wan

Interdependence is a fundamental ingredient to analyze the stability of many real-world complex systems featuring functional liasons. Yet, physical realizations of this coupling are still unknown, due to the lack of a theoretical framework…

Disordered Systems and Neural Networks · Physics 2024-12-04 Ivan Bonamassa , Bnaya Gross , Shlomo Havlin

We study the influence of the softness of the interparticle interactions on the fragility of a glass former, by considering three model binary mixture glass formers. The interaction potential between particles is a modified Lennard-Jones…

Disordered Systems and Neural Networks · Physics 2012-06-19 Shiladitya Sengupta , Filipe Vasconcelos , Frédéric Affouard , Srikanth Sastry

This study aims to develop a deep learning model for predicting the binding affinity of ligands targeting the Peroxisome Proliferator-Activated Receptor (PPAR) family, using 2D molecular descriptors. A dataset of 3,764 small molecules with…

Biomolecules · Quantitative Biology 2024-12-31 La Ode Aman , Aiyi Asnawi
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