24 papers · ranked by Valyu relevance
Nate Bade, Lindsay Erickson
Sensitivity analysis is an important component of simulation-based decision support because it helps analysts determine which inputs most strongly influence model outcomes under uncertainty. This paper organizes the broad sensitivity analysis literature into a coherent framework for use in complex simulation settings…
Arnald Puy, Andrea Saltelli
While sensitivity analysis improves the transparency and reliability of mathematical models, its uptake by modelers is still scarce. This is partially explained by its technical requirements, which may be hard to understand and implement by the nonspecialist. Here we propose a sensitivity analysis approach based on the…
Rachel Mester, Alfonso Landeros, Chris Rackauckas, Kenneth Lange
Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty, and forecasting the results of both thought and lab experiments. Although there are many methods currently available for performing differential sensitivity analysis of biological models, it can be difficult to…
Alon Korngreen
Markov models are widely used to describe the gating kinetics of voltage-gated ion channels, but increasing model complexity can introduce parameters that are difficult to constrain from macroscopic measurements. In this study, I used global variance-based Sobol sensitivity analysis to examine how model topology…
Yang Yang, Haiyan Liu, Qichun Zhang
The disease-information coupling propagation dynamics model is a widely used model for studying the spread of infectious diseases in society, but the parameter settings and sensitivity are often overlooked, which leads to enlarged errors in the results. Exploring the influencing factors of the disease-information…
Sarah Iaquinta, Shahram Khazaie, Samer Albanna, Sylvain Fréour + 1 more
'Frédéric Jacquemin'] Title: ABSTRACT Experimental studies on the cellular uptake of nanoparticles (NPs), useful for the investigation of NP-based drug delivery systems, are often difficult to interpret due to the large number of parameters that can contribute to the phenomenon. It is therefore of great interest to…
Gathani, Sneha, Li, Kevin + 12 more
SNEHA GATHANI, University of Maryland, College Park, USA KEVIN LI, University of Maryland, College Park, USA RAGHAV THIND, University of Maryland, College Park, USA SIRUI ZENG, University of Maryland, College Park, USA MATTHEW XU, University of Maryland, College Park, USA PETER J. HAAS, University of Massachusetts…
Karolina Tlałka, Harry Saxton, Ian Halliday, Xu Xu + 4 more
'Andrew Narracott' 'Daniel Taylor' 'Maciej Malawski' 'Daniel A Beard'] The baroreflex is one of the most important control mechanisms in the human cardiovascular system. This work utilises a closed-loop in silico model of baroreflex regulation, coupled to pulsatile mechanical models with (i) one heart chamber and…
E. Machado, Jakob L. Andersen, Rolf Fagerberg, Daniel Merkle
In this study, we introduce a sensitivity analysis methodology for stochastic systems in chemistry, where dynamics are often governed by random processes. Our approach is based on gradient estimation via finite differences, averaging simulation outcomes, and analyzing variability under intrinsic noise. We characterize…
Wee Hao Ng, Christopher R. Myers, Scott McArt, Stephen P. Ellner
Sensitivity analysis is often used to help understand and manage ecological systems, by assessing how a constant change in vital rates or other model parameters might affect the management outcome. This allows the manager to identify the most favorable course of action. However, realistic changes are often localized in…
Rachel Mester, Alfonso Landeros, Chris Rackauckas, Kenneth Lange + 1 more
Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty, and forecasting the results of both thought and lab experiments. Although there are many methods currently available for performing differential sensitivity analysis of biological models, it can be difficult to…
Mariia Kozlova, Antti Ahola, Pamphile T. Roy, Julian Scott Yeomans
Models of complex technological systems inherently contain interactions and dependencies among their input variables that affect their joint influence on the output. Such models are often computationally expensive and few sensitivity analysis methods can effectively process such complexities. Moreover, the sensitivity…
Peter J. Gawthrop, Michael Pan
The sensitivity of systems biology models to parameter variation can give insights into which parameters are most important for physiological function, and also direct efforts to estimate parameters. However, in general, kinetic models of biochemical systems do not remain thermodynamically consistent after perturbing…
Zahra Sadeghi, Stan Matwin
study on Digit Classification Authors: ['Zahra Sadeghi' 'Stan Matwin'] Global sensitivity analysis (GSA) aims to detect influential input factors that lead a model to arrive at a certain decision and is a significant approach for mitigating the computational burden of processing high dimensional data. In this paper, we…
Dominik Duleba, Adria Martínez-Aviñó, Andriy Revenko, Robert P. Johnson
Sensitivity in Nanoscale Sensing Devices Authors: Dominik Duleba, Adria Martínez-Aviñó, Andriy Revenko, Robert P. Johnson In nanoscale sensors, understanding and predicting sensor sensitivity is challenging as the physical phenomena that govern the transduction mechanism are often highly nonlinear and highly coupled.…
Awino Maureiq E. Ojwang’, Sarah Bazargan, Joseph O. Johnson, Shari Pilon-Thomas + 1 more
A hybrid off-lattice agent-based model has been developed to reconstruct the tumor tissue oxygenation landscape based on histology images and simulated interactions between vasculature and cells with microenvironment metabolites. Here, we performed a robustness sensitivity analysis of that model’s physical and…
Nate Kornetzke, Helen J. Wearing
Emerging infectious diseases are a persistent public health threat that challenge deterministic, mechanistic modeling approaches. Because outbreaks initially start with a low number of infected hosts, their dynamics are highly stochastic, making traditional deterministic methods, e.g. ordinary differential equations…
Kelsey I. Gasior, Nicholas G. Cogan
Liquid-liquid phase separation is an intracellular mechanism by which molecules, usually proteins and RNAs, interact and then rapidly demix from the surrounding matrix to form membrane-less compartments necessary for cellular function. Occurring in both the cytoplasm and the nucleus, properties of the resulting…
Mitchel J. Colebank, Daniele Enrico Schiavazzi
Computational inverse problems for biomedical simulators suffer from limited data and relatively high parameter dimensionality. This often requires sensitivity analysis, where parameters of the model are ranked based on their influence on the specific quantities of interest. This is especially important for simulators…
Itamar Borges Jr, Júlio César Duarte, Romulo Dias da Rocha
We decomposed density functional theory charge densities of 53 nitroaromatic molecules into atom-centered electric multipoles using the distributed multipole analysis that provides a detailed picture of the molecular electronic structure. Three electric multipoles, ∑▒〖Q_0 (NO_2)〗 (the charge of the nitro groups)…
Authors not listed
Amines play a significant role in everyday life, and their detection remains a crucial focus in research and development. Although conducting polymer-based gas sensors have been widely reported for amine detection using DC resistivity measurements, they often lack selectivity to distinguish between intragroup…
Justus T. Metternich, Björn Hill, Janus A. C. Wartmann, Chen Ma + 4 more
Enzymatic reactions are used to detect analytes in a range of biochemical methods such as enzyme-linked immunosorbent assays (ELISAs). To measure the presence of an analyte, they are conjugated to a recognition unit and convert a substrate into a (colored) product that is detectable by visible (VIS) light. Thus, the…
Authors not listed
Single-walled carbon nanotubes (SWCNTs) are powerful building blocks for near-infrared (NIR) fluorescent biosensors. They can be chemically tailored to detect specific biomolecules. Their performance in (bio)imaging applications depends on how fast analytes bind and unbind and change their fluorescence but measuring…
Justus T. Metternich, Sujit K. Patjoshi, Tanuja Kistwal, Sebastian Kruss
Optical sensors/probes are powerful tools to identify and image (biological) molecules. Because of their optoelectronic properties, nanomaterials are often used as building blocks. Such nanosensors are assembled from an optically sensitive nanomaterial, a (biological) recognition unit, and linker chemistry that…