27 papers · ranked by Valyu relevance
Belding, Juliana, Quinn, Keaton
Working with letters that represent unknown constants, i.e., parameters, has been historically challenging for students. This is an important skill for their success in many future quantitative settings, and yet it appears this topic is rarely included explicitly in math curricula. We argue that we should be explicitly…
Gabriele Lillacci, Mustafa Khammash, Anand R. Asthagiri
A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants) are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course…
Giuseppe Longobardi, Alessandro Treves
Parametric approaches to grammatical diversity range from Chomsky's 1981 classical Principles & Parameters model to minimalist reinterpretations: in some proposals of the latter framework, parameters need not be an extensional list given at the initial state S0 of the mind, but can be constructed through a bio-program…
Yingyi Zhang, Chang Liu, Yu-Pin Lin, Marta Otero
Parametric thinking has found wide acceptance in both the building industry and environmental sciences. In the context of environmental urban morphology however, parametric thinking has been neglected. This paper critically assesses environmental optimization with a focus on parametric urbanism. The analysis addresses…
Daniel Kaschek, Wolfgang Mader, Mirjam Fehling-Kaschek, Marcus Rosenblatt + 1 more
In a wide variety of research elds, dynamic modeling is employed as an instrument to learn and understand complex systems. The differential equations involved in this process are usually non-linear and depend on many parameters whose values decide upon the characteristics of the emergent system. The inverse problem…
Geethu Joy, Christian Huyck, Xin‐She Yang
Almost all optimization algorithms have algorithm-dependent parameters, and the setting of such parameter values can largely influence the behaviour of the algorithm under consideration. Thus, proper parameter tuning should be carried out to ensure the algorithm used for optimization may perform well and can be…
Riley Hickman, Priyansh Parakh, Austin Cheng, Qianxiang Ai + 3 more
Experiment planning algorithms are a required component of autonomous platforms for scientific discovery. Selecting a suitable optimization algorithm for a novel application is an important yet difficult choice a researcher has to make based on past empirical performance on similar tasks. To facilitate the evaluation…
Omid Ghasemi, Merry L Lindsey, Tianyi Yang, Nguyen Nguyen + 2 more
'Yufei Huang' 'Yu-Fang Jin'] Background The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been…
César Parra-Rojas, Esteban A. Hernandez-Vargas
Partial differential equations (PDEs) is a well-established and powerful tool to simulate multi-cellular biological systems. However, available free tools for validation against data are not established. The PDEparams module provides flexible functionality in Python for parameter estimation in PDE models. The PDEparams…
Ryoji Tanabe
Since the scale factor and the crossover rate significantly influence the performance of differential evolution (DE), parameter adaptation methods (PAMs) for the two parameters have been well studied in the DE community. Although PAMs can sufficiently improve the effectiveness of DE, PAMs are poorly understood (e.g.…
Alexey Kazarnikov, Nadja Ray, Heikki Haario, Joona Lappalainen + 1 more
'Andreas Rupp'] Abstract. Self organizing complex systems can be modeled using cellular automaton models. However, the parametrization of these models is crucial and significantly determines the resulting structural pattern. In this research, we introduce and successfully apply a sound statistical method to estimate…
Nathaniel J. Linden, Boris Kramer, Padmini Rangamani
Dynamical systems modeling, particularly via systems of ordinary differential equations, has been used to effectively capture the temporal behavior of different biochemical components in signal transduction networks. Despite the recent advances in experimental measurements, including sensor development and ‘-omics’…
Joshua Horton, Alice Allen, Leela Dodda, Daniel Cole
Modern molecular mechanics force fields are widely used for modelling the dynamics and interactions of small organic molecules using libraries of transferable force field parameters. For molecules outside the training set, parameters may be missing or inaccurate, and in these cases, it may be preferable to derive…
Pedro Á. Castillo, M. G. Arenas, Núria Rico, Antonio M. Mora + 3 more
'Pablo García‐Sánchez' 'Juan Luís Jiménez Laredo' 'J. J. Merelo'] When search methods are being designed it is very important to know which parameters have the greatest influence on the behaviour and performance of the algorithm. To this end, algorithm parameters are commonly calibrated by means of either theoretic…
Qianqian Tong, Zhiyong Yuan, Mianlun Zheng, Xiangyun Liao + 2 more
'Weixu Zhu' 'Guian Zhang'] The elastic parameters of soft tissues are important for medical diagnosis and virtual surgery simulation. In this study, we propose a novel nonlinear parameter estimation method for soft tissues. Firstly, an in-house data acquisition platform was used to obtain external forces and their…
Jonathan Shimwell, John Billingsley, Rémi Delaporte-Mathurin, Declan Morbey + 3 more
'Declan Morbey' 'Matthew Bluteau' 'Patrick Shriwise' 'Andrew Davis'] During the conceptual design process of fusion reactors it is useful to rapidly prototype different design concepts and assess their suitability against a range of high level requirements. Rapid prototyping allows the 'fail early' mantra of other…
Ankush Aggarwal
Several nonlinear and anisotropic constitutive models have been proposed to describe the biomechanical properties of soft tissues, and reliably estimating the unknown parameters in these models using experimental data is an important step towards developing predictive capabilities. However, the effect of parameter…
Hong Qin
Parameter identification is an important branch of automatic control. Due to its special function, it has been widely used in various fields, especially the modeling of complex systems or systems whose parameters are not easy to determine. With the development of control technology, the scale of the control object is…
Harry Saxton, Xu Xu, Torsten Schenkel, Richard H. Clayton + 1 more
Dynamical system models typically involve numerous input parameters whose “effects” and orthogonality need to be quantified through sensitivity analysis, to identify inputs contributing the greatest uncertainty. Whilst prior art has compared total-order estimators’ role in recovering “true” effects, assessing their…
Robert Arbon, Yanchen Zhu, Antonia S. J. S. Mey
Markov state models (MSM) are a popular statistical method for analyzing the conformational dynamics of proteins, including protein folding. With all statistical and machine learning (ML) models choices must be made about the modeling pipeline that cannot be directly learned from the data. These choices, or…
Authors not listed
While the intrinsically multi-scale nature of most advanced materials necessitates the use of cost-effective computational models based on classical physics, a reliable description of the structure and dynamics of their components often requires a quantum-mechanical treatment. In this work, we present JOYCE3.0, a…
MT Cabeleira, S Ray, NC Ovenden, V Diaz-Zuccarini
Calibration of mechanistic cardiovascular models is a central barrier to their use in population analysis and patient-specific simulation, particularly in settings where key physiological variables are unobservable and multiple parameter combinations can reproduce the same haemodynamic targets. In this work, we present…
Simon Boothroyd, Pavan Kumar Behara, Owen Madin, David Hahn + 15 more
Simon Boothroyd 2 , Pavan Kumar Behara 1 , Owen Madin 3 , David Hahn 4 , Hyesu Jang5,6 , Vytautas Gapsys4,7 , Jeffrey Wagner 1,8 , Joshua Horton 9 , David Dotson10,8 , Matthew Thompson3,8 , Jessica Maat 1 , Trevor Gokey 1 , Lee-Ping Wang 5 , Daniel Cole 9 , Michael Gilson 11 , John Chodera 12 , Christopher Bayly 6 …
Owen Madin, Michael Shirts
Dispersion-repulsion interactions, commonly represented in atomistic force fields by the Lennard-Jones (LJ) potential, play an important role in the accuracy of molecular simulations. Training the force field parameters used in the LJ potential is challenging, generally requiring adjustment based on simulations of…
Eric Hermes, Khachik Sargsyan, Habib Najm, Judit Zádor
We present a new algorithm for the optimization of molecular structures to saddle points on the potential energy surface using a redundant internal coordinate system. This algorithm automates the procedure of defining the internal coordinate system, including the handling of linear bending angles, e.g. through the…
Yudong Qiu, Daniel Smith, Chaya Stern, Mudong Feng + 1 more
The parameterization of torsional / dihedral angle potential energy terms is a crucial part of developing molecular mechanics force fields. Quantum mechanical (QM) methods are often used to provide samples of the potential energy surface (PES) for fitting the empirical parameters in these force field terms. To ensure…
Samson Ali, Adrian Koh, David Popp, Kotaro Tanaka + 6 more
ParMs generally exist on low copy number plasmids where they contribute to plasmid segregation and stable inheritance. We carried out bioinformatics analysis, which indicated that ParM genes are not only confined to plasmids but are also occasionally found on genomes. Here we report the discovery and characterization…