• A new approach of model parameter estimation is used with simulated measurements to recover both biological and economic input parameters of a natural resource model. (snf.no)
  • The data assimilation technique is the variational adjoint method (VAM) for parameter estimation. (snf.no)
  • We demonstrate the utility of parameter significance discrimination as applied to parameter estimation. (tufts.edu)
  • A novel method for embedded hardware-based parameter estimation of the Cole model of bioimpedance is developed and presented. (nature.com)
  • Read about inconsistency in assessment model results and why caution is needed even with high accuracy in parameter estimation. (ices.dk)
  • Specifically, we propose BO for efficient parameter estimation of a dynamic microalgae metabolism model (Baroukh et al. (imperial.ac.uk)
  • we are specifically interested in running the simulation model many times for parameter estimation. (imperial.ac.uk)
  • In biological parameter estimation, Bayesian Optimisation (BO) is challenging because the parameters interact nonlinearly and the broad parameter bounds result in a huge search space. (imperial.ac.uk)
  • Numerical simulation techniques coupled to parameter estimation methods aim at predicting and optimizing therapies efficacy. (ens-lyon.fr)
  • Proposed library can be used for recursive parameter estimation of linear dynamic models ARX, ARMAX and OE. (wseas.org)
  • More realistic versions of this model and improved estimates of parameters from surveillance data will strengthen the estimation of the burden of influenza. (who.int)
  • This perspective article highlights the pros and cons of using simple (often identifiable) vs. complex (more physiologically detailed but often non-identifiable) models, as well as aspects of parameter identifiability, sensitivity and inference methodologies for model development and analysis. (stir.ac.uk)
  • My current reseach focuses on parameter inference and uncertainty quantificaiton in complex biological systems, using methods from machine learning, computational statistics and emulation. (gla.ac.uk)
  • Model predictions or model-based inference that use parameters from these efficient algorithms are considered reliable and optimal. (ices.dk)
  • For fish stock assessment models, this may lead to erroneous inference about population size, and wrong estimates of parameters that are central to management. (ices.dk)
  • are aware of the importance of all steps in the processes of scientific inference, from formulating the biological question, to designing the study, analyzing the data and interpreting the results statistical analysis. (uit.no)
  • A central challenge in computational modelling of dynamic biological systems is parameter inference from experimental time course measurements. (warwick.ac.uk)
  • Research on Inference theory is on inference for infinite dimensional problems, i.e. problems when the unknown parameter lies in function classes, and on particle filters and state space models. (lu.se)
  • Some research areas are: limit theorems in mathematical statistics, for instance limit distributions for regular and nonregular statistical functionals, order restricted inference, nonparametric methods for dependent data, in particular strong (long range) and weak dependence for stationary processes, nonparametric methods for hidden Markov chains and state space models. (lu.se)
  • other models are more detailed and account for sub-cellular processes. (wikipedia.org)
  • In particular, it is increasingly recognized that commonly used ODE models are not able to capture the stochastic nature of many cellular processes. (biorxiv.org)
  • Mechanistic models are commonly used to acquire insights about the biochemical reaction networks that govern cellular processes inside a cell. (biorxiv.org)
  • They typically consist of several interrelated equations to describe complex biological and ecological processes. (ices.dk)
  • The course aims to demonstrate how biological theory, study designs and analyses should be linked, and the course should make students able to plan and conduct empirical, biological research through all stages of the research processes from formulation of hypotheses to the presentation of the results. (uit.no)
  • Dynamic models of biological processes allow us to test biological hypotheses while running fewer costly, real-world experiments. (imperial.ac.uk)
  • This model has the potential to address the different sources of variability that are relevant to transcriptional and translational processes at the molecular level, namely, intrinsic noise due to the stochastic nature of the birth and deaths processes involved in chemical reactions, and extrinsic noise arising from the cell-to-cell variation of kinetic parameters associated with these processes. (warwick.ac.uk)
  • Cell migration plays a critical role in a number of biological processes such as embryonic development, wound healing, and immune response. (clarkson.edu)
  • The models in this category can be either deterministic or probabilistic. (wikipedia.org)
  • Modelling deterministic networks. (bio.net)
  • One possible way forward out of this situation is to use computer modeling and simulation of breeding programs in lieu of deterministic models. (usda.gov)
  • Current interests of the group include representing uncertainty in optimisation models, designing numerical optimisation algorithms and computational software frameworks, and applying these algorithms to energy production, capacity planning, manufacturing and distribution models under uncertainty, financial engineering and risk management. (imperial.ac.uk)
  • Generative models are a large group of algorithms for machine learning that make predictions by modeling the joint distribution of P (y, x). (washingtonindependent.com)
  • In unsupervised machine learning, generative modeling algorithms analyze large amounts of training data and reduce them to their digital essence. (washingtonindependent.com)
  • The latter now also include modelling algorithms for generating three-dimensional models from solution scattering data that provide results in the form of bead or atomic coordinates. (iucr.org)
  • Using identical twin experiments, it is shown that the parameters of the model can be retrieved. (snf.no)
  • To accelerate the convergence to a unified theory, we list several models in each category, and where applicable, also references to supporting experiments. (wikipedia.org)
  • The proposed approach is inspired by the classic Design of Experiments (DOE) techniques, performed in silico using a preliminary model. (tufts.edu)
  • We start by defining the possible ranges of each of the unknown model parameters, design a set of in-silico experiments or, equivalently, a set of selected calculations that are simulated through the preliminary model. (tufts.edu)
  • A D-optimal design of experiments was used to sample the parameters across their ranges, and a RSM was obtained with antibody flux as the output. (tufts.edu)
  • Sampling strategies of observational data from biological systems Principles of biological experiments Introduction to statistical modelling of biological data with emphasis on general and generalised linear models. (uit.no)
  • The use of this methodology for validating mathematical models from experimental data and designing new experiments is discussed. (researchgate.net)
  • In this project, the biological members will use microbial experiments to quantify the effects of spatial structure and heterogeneity on ecological and evolutionary dynamics. (clarkson.edu)
  • Data from experiments will be utilized by the mathematical members to both formulate and calibrate mathematical models of bacterial movement. (clarkson.edu)
  • In our biological experiments we used 50 MHz and 64 MHz since this is approved in MRI systems. (intechopen.com)
  • The course covers theoretical models for the structure and reactions of atomic nuclear, as well as experiments in nuclear physics and their scientific applications. (lu.se)
  • The model successfully describes the kinetics of experimental data and also correctly predicts the behavior in experiments where the system is perturbed. (lu.se)
  • We compare the models meters where only a few (if any) have values that represent both to existing data (9,10) and to novel measurements first reliable estimates from experiments. (lu.se)
  • The experiments consist of kinetic (time- kinetic data is typically not sufficient to constrain the course) measurements after TGF-b stimulation under differ- parameter values to a single optimal solution, and multiple ent conditions: untreated cells and three cases in which parameter sets can explain the available data. (lu.se)
  • Two of the experiments are used to fit the model parameters sets, where these sets subsequently are clustered with and the other two are left as ``blind test'' experiments. (lu.se)
  • In this paper, we develop a theoretical model which shows that under certain conditions of environmental stochasticity, selection actually favors sensors of lower accuracy. (nature.com)
  • He combines this with theoretical modelling of nanocomponents for photovoltaics and sub-wavelength focusing of light both by his own group and in collaborations. (lu.se)
  • He combines this with theoretical modelling of nanocomponents for photovoltaics and creating new architectures for light emitting diodes, breaking the limits of ray optics and avoiding the challenge of total internal reflection. (lu.se)
  • better source needed] Modeling helps to analyze experimental data and address questions. (wikipedia.org)
  • All of the parameters in the model are based on experimental data related to the biology and ecology of the virus, mosquito vector, and bird host. (infectioncontroltoday.com)
  • However, this increases the number of parameters that need to be identified from experimental data and introduces a substantial challenge in the identification of the important model parameters. (tufts.edu)
  • As more details are added to the model, the increased number of parameters implies the necessity of an increased amount of experimental data. (tufts.edu)
  • However, more experimental data does not imply that the values of the insignificant parameters can be easily determined. (tufts.edu)
  • These models are typically obtained by a combination of expert and literature-driven knowledge as well as experimental data. (biorxiv.org)
  • We consider estimating biological parameters (e.g., reaction rate kinetics) by minimising the squared error between model and experimental data points. (imperial.ac.uk)
  • The availability of multiple single cell data provides a unique opportunity to estimate such a model and explicitly quantify the sources of variation from experimental data. (warwick.ac.uk)
  • The neointimal area predicted by the model demonstrates a good agreement with the detailed experimental data. (springer.com)
  • It should be noted that including vessel curvature and ECM production in the model was paramount to obtain a good agreement with the experimental data. (springer.com)
  • Due to the high problem dimensionality (in this context, 10 parameters), balancing exploration versus exploitation becomes more intricate and traditional Bayesian methods do not scale well. (imperial.ac.uk)
  • Two partition methods were used to stratify the data sets for training, validating and testing the prediction models. (cdc.gov)
  • June 19, 2018 - Notice of Addition of Letter of Intent Due Dates on BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain (R01 Clinical Trial Not Allowed). (nih.gov)
  • March 19, 2018 - Notice of Change to Expiration Date on BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain (R01 Clinical Trial Not Allowed). (nih.gov)
  • Another approach for reliability assessment is based on Markovian model and system state graph and was developed to overcome limitations of logical-and-probabilistic methods that are suitable only for systems with hot standby. (wseas.org)
  • In this paper, we introduced two methods of ultrasound elastomicroscopy using water jet and osmosis loading for imaging the elasticity of biological soft tissues with high resolutions. (who.int)
  • It provides an ensemble of high quality solutions, which are analyzed with clustering methods and display a hierarchical structure highlighting distinct parameter subspaces with biological interpretations. (lu.se)
  • In unsupervised methods, providing explanatory insights into addition, we predict the response of the system when varying the data and related biological interpretations. (lu.se)
  • Barbara Webb studies perceptual systems for the control of behaviour, by building computational and physical (robot) models of the hypothesised mechanisms. (lu.se)
  • Abstract: Kinetic modeling for metabolic networks, formulated as a set of ordinary differential equations for intracellular species concentrations, provides the ability to simulate the dynamic behavior of cellular metabolism. (tufts.edu)
  • Abstract: The primary goal of this research project was to demonstrate the feasibility of developing an optimal prediction model for noise -induced hearing loss (NIHL) using a radial basis function neural network (RBFNN). (cdc.gov)
  • ABSTRACT The burden of influenza was estimated from surveillance data in Tunisia using epidemiological parameters of transmission with WHO classical tools and mathematical modelling. (who.int)
  • The paper distills the central themes of the issue of identifiability and optimal model size and discusses open challenges. (stir.ac.uk)
  • The optimal value for parameter α is estimated using a brute force method. (nature.com)
  • Ignoring such inconsistencies may result in non-optimal parameter estimates, wrongly calibrated models, and erroneous model-based decisions. (ices.dk)
  • Optimal parameter estimates were found by minimising the model mean squared error. (cdc.gov)
  • Hyperelastic materials are widely used in many applications such as biological tissues, polymeric foams, and moreover. (easychair.org)
  • It is widely applied to characterize biological tissues, where the measured impedance is often referred to as tissue bioimpedance 2 . (nature.com)
  • In addition to biological tissues, these systems have potential applications for the assessment of bioengineered tissues, biomaterials with fine structures, or some engineering materials. (who.int)
  • Sher A, Niederer SA, Mirams GR, Kirpichnikova A, Allen R, Pathmanathan P, Gavaghan DJ, Van Der Graaf PH & Noble D (2022) A Quantitative Systems Pharmacology perspective on the importance of parameter identifiability. (stir.ac.uk)
  • There is an inherent tension in Quantitative Systems Pharmacology (QSP) between the need to incorporate mathematical descriptions of complex physiology and drug targets with the necessity of developing robust, predictive and well-constrained models. (stir.ac.uk)
  • Engineering principles for environmental preservation and management, pollution control, life-cycle assessment, interactions in the macro and micro-environments, global and ecological systems, social-economic factors in environmental systems, predictive models for the current and future environment, environmental engineering as the driver of economic systems. (up.ac.za)
  • PROGRAM: - Complex Biological Systems: Modelling Relations: Historical and conceptual introduction. (bio.net)
  • Complex Biological Systems: Applied Network Theory: Nodes, links and types of networks. (bio.net)
  • Complex Biological Systems: Network Properties: Robustness and the concept of secondary extinction. (bio.net)
  • Solving the chemical master equation is an indispensable tool in understanding the behavior of biological and chemical systems. (biorxiv.org)
  • The approach is guided by partitioning the network into biological relevant subsets and thus avoids the use of single species basis functions that are known to give inaccurate results for biological systems. (biorxiv.org)
  • Mathematical models of physical and biological systems contain parameters that need to be estimated from measured data. (sbir.gov)
  • The methodology will be illustrated by estimating parameters governing the diffusion approximations of some interesting systems biological models. (videolectures.net)
  • For over a decade, MapReduce has become a prominent programming model to handle vast amounts of raw data in large scale systems. (iccs-meeting.org)
  • CMSB 2022 solicits original research articles, tool papers, posters, and highlight talks on the modelling and analysis of biological systems and networks as well as the analysis of biological data. (unibuc.ro)
  • Mathematical members will utilize both mechanistic principles and individual cell data to discover interaction rules in many-particle biological systems that depend on both local interactions and environmental factors. (clarkson.edu)
  • Temperature has a direct effect on fundamental biological systems, including enzyme activity and correct folding of proteins. (springer.com)
  • However, several approaches can be distinguished, from more realistic models (e.g., mechanistic models) to more pragmatic models (e.g., phenomenological models). (wikipedia.org)
  • Here we present a proof-of-concept study using the European anchovy as a model species that shows how a trait-based, mechanistic species distribution model can be used to explore the vulnerability of marine species to environmental changes, producing quantitative outputs useful for informing fisheries management. (frontiersin.org)
  • We crossed scenarios of temperature and food to generate quantitative maps of selected mechanistic model outcomes (e.g. (frontiersin.org)
  • In addition to this there is no "gold standard" for model development and assessment in QSP. (stir.ac.uk)
  • The ADMB/TMB platforms currently used for fisheries modelling and stock assessment are built on such an algorithm. (ices.dk)
  • The input stage of these models is not electrical, but rather has either pharmacological (chemical) concentration units, or physical units that characterize an external stimulus such as light, sound or other forms of physical pressure. (wikipedia.org)
  • We describe a computational methodology allowing to systematically and quantitatively characterize a Boolean mathematical model of a biological network in terms of genetic interactions between all loss of function and gain of function mutations with respect to all model phenotypes or outputs. (researchgate.net)
  • The present paper presents a computationally efficient methodology to identify the model parameters that are highly significant for the model predictions and thus distinguish them from the insignificant ones. (tufts.edu)
  • We applied this methodology to a dynamic model of Chinese hamster ovary (CHO) cell metabolism (Nolan, 2011). (tufts.edu)
  • Through this parameter significance methodology, we were able to discriminate the highly significant parameters from the highly insignificant parameters. (tufts.edu)
  • We demonstrate this methodology on three published models for each of which we derive the genetic interaction networks and analyze their properties. (researchgate.net)
  • The approach presented here provides a very detailed, location-specific, validation methodology for in silico restenosis models. (springer.com)
  • We present a two-dimensional continuous-time Bayesian hierarchical model based on van Kampen's linear noise approximation. (warwick.ac.uk)
  • This study demonstrates that model predictions based on functional traits can reduce the degree of uncertainty when forecasting future trends of fish stocks. (frontiersin.org)
  • We used uncertainty and sensitivity analysis of the basic reproductive number R 0 to assess the role that model parameters play in outbreak control. (cdc.gov)
  • know how to interpret parameters estimated using statistical models, and how to interpret and deal with uncertainty. (uit.no)
  • know how to use generalized linear models (linear regression, ANOVA, ANCOVA, logistic regression, log-linear models) and how to interpret parameter estimates and their uncertainty. (uit.no)
  • One would like not only to measure mean parameter values but also estimate the uncertainty of single cell values and the variability from cell to cell. (warwick.ac.uk)
  • New data on COVID-19 are available daily, yet information about the biological aspects of SARS-CoV-2 and epidemiological characteristics of COVID-19 remain limited, and uncertainty remains around nearly all parameter values. (cdc.gov)
  • It efficiently combines time series of artificial data with a simple bioeconomic fisheries model to optimally estimate the model parameters. (snf.no)
  • The procedure provides an efficient way of calculating poorly known model parameters by fitting model results to simulated data. (snf.no)
  • We found that the method was able to reliably recover parameters after few iterations, and that modest noise added to the data had little effect on the estimated parameters and on the rate of convergence. (actapress.com)
  • Predictions with converged parameters showed excellent agreement with the data in both cases. (actapress.com)
  • With the specific parameters of that disease, DYCAST was able to predict its spread in the city of Riberão Preto in Brazil, Carney said, citing unpublished data. (infectioncontroltoday.com)
  • Modelling networks from loaded data. (bio.net)
  • The traditional approaches for processing bioimpedance data can be broadly sorted into two categories: discrete processing and equivalent circuit modeling. (nature.com)
  • The second approach uses equivalent electrical circuits, composed of electrical elements (such as resistors, capacitors and inductors), to represent multi-frequency bioimpedance data and then investigates the relationship of the model/component values to underlying physical and electrochemical changes in the tissue. (nature.com)
  • can decide on which statistical models should be used based on assumptions and data characteristics. (uit.no)
  • There are several timescales for collecting microalgae metabolism data: an experiment may take 10 days while each model simulation of Baroukh et al. (imperial.ac.uk)
  • We report on an approach for validation of an in silico 3D model of in-stent restenosis in porcine coronary arteries and illustrate this approach by comparing the modelling results to in vivo data for 14 and 28 days post-stenting. (springer.com)
  • A generative model looks at how the data is spread out and tells how likely something will happen. (washingtonindependent.com)
  • When it comes to analyzing neuroscientific data, generative models have better properties. (washingtonindependent.com)
  • In unsupervised machine learning, generative modeling represents phenomena in data, allowing computers to grasp the current world. (washingtonindependent.com)
  • This AI knowledge may be used to estimate various probabilities about a topic based on modeled data. (washingtonindependent.com)
  • Neural networks then use these simplified core understandings of real-world data to model data that looks like or is the same as real-world data. (washingtonindependent.com)
  • In contrast to discriminative modeling, generative modeling identifies existing data and may be used to categorize data. (washingtonindependent.com)
  • Discriminative modeling identifies tags and arranges data, while generative modeling creates something. (washingtonindependent.com)
  • Models developed using the data provided in the planning scenario tables can help evaluate the potential effects of different community mitigation strategies (e.g., social distancing). (cdc.gov)
  • All parameter values are based on current COVID-19 surveillance data and scientific knowledge. (cdc.gov)
  • The parameter values used in these scenarios are likely to change as we obtain additional data about the upper and lower bounds of disease severity and the transmissibility of SARS-CoV-2, the virus that causes COVID-19. (cdc.gov)
  • Scenario 5 represents a current best estimate about viral transmission and disease severity in the United States, with the same caveat: the parameter values will change as more data become available. (cdc.gov)
  • Studies of the translocation of inhaled nanoparticle s from rodent lungs to different target organs provide data to model the inhalation and translocation of nanoparticle s. (cdc.gov)
  • Data from two different studies in rats (one endotracheal instillation and one inhalation exposure) were used to calibrate the model. (cdc.gov)
  • The overall fit of the model to the total measured particle mass in the body was very good for both studies (R2=0.98-0.99), although different parameter estimates were sometimes required to fit the study-specific data. (cdc.gov)
  • While this model describes the retention and translocation of nanoparticle s from the lungs reasonably well, further model evaluation and validation is needed using additional data. (cdc.gov)
  • The model was developed to predict noise -induced hearing loss (NIHL) from an archive of animal noise exposure data, which contains 900 chinchillas exposed to various noise environments. (cdc.gov)
  • Comprehensive experimental results show that our proposed model is very efficient for mining share-frequent patterns from WSN data in terms of time and scalability. (iccs-meeting.org)
  • This FOA solicits new theories, computational models, and statistical tools to derive understanding of brain function from complex neuroscience data. (nih.gov)
  • The omission of these important data can lead to inaccurate structural parameters and the generation of erroneous and misleading structural models, the validity of which cannot be independently assessed. (iucr.org)
  • In parallel, a Small-Angle Scattering Task Force has been established to advise the Protein Data Bank on whether models based on SAS data analysis should be deposited and, if so, in what format and with what kinds of supporting data and validation. (iucr.org)
  • An alternate approach is to track the dynamics of live cells through time-lapse imaging and utilize knowledge based data-driven modeling to understand the individual and collective behavior of cells at high spatio-temporal precision. (clarkson.edu)
  • In this project, biological members will work to generate in vivo confocal imaging data of the developing spot pattern, as well as generate pupae that express RNAi targeting modiers in the dorsal thorax. (clarkson.edu)
  • A novel method in this context, simulated tempering, is used to fit the model parameters to the data. (lu.se)
  • 2. Find values for the kinetic parameters from experimental b pathway have been detected in several human diseases, estimates or by fitting the model to experimental kinetic most notably in many forms of cancer, and in fibrotic diseases data. (lu.se)
  • Thus, we develop a predictive model that is tested against existing data. (lu.se)
  • To further this information, it is generally assumed that 100% of the investigate how bioavailability data could be used in setting OELs, inhaled mass is deposited in the respiratory tract and com- a preliminary pharmacokinetic (PK) model was developed to pletely absorbed. (cdc.gov)
  • In this paper we propose a dynamical low-rank approach that enables the simulation of large biological networks. (biorxiv.org)
  • B) TOOL PAPERS: Tool papers should present new tools or public websites, new tool components or novel extensions to existing tools or websites supporting biological system modelling, analysis, simulation, or similar. (unibuc.ro)
  • 3. Analyze the behavior of the model for extracted param- too large for modeling, since there are a sufficient number of eter values. (lu.se)
  • In particular, these models describe how the voltage potential across the cell membrane changes over time. (wikipedia.org)
  • The models in this category describe the relationship between neuronal membrane currents at the input stage, and membrane voltage at the output stage. (wikipedia.org)
  • The term hypoxia is used to describe biological situations where insufficient levels of oxygen exist. (mdpi.com)
  • However, it is also well known that in a number of problems the ODE formulation is insufficient to describe important features of the biological system [ 48 , 25 , 36 , 38 ]. (biorxiv.org)
  • 0.RESULT:We describe a configurable tool to explore generalizations of the standard Markov model. (umd.edu)
  • A generative model could be a set of equations that describe how human patient signals change over time based on how the system works. (washingtonindependent.com)
  • Development of a bio-mathematical model in rats to describe clearance, retention and translocation of inhaled nano particles throughout the body. (cdc.gov)
  • BACKGROUND:The currently used kth order Markov models estimate the probability of generating a single nucleotide conditional upon the immediately preceding (gap = 0) k units. (umd.edu)
  • These values--called parameter values -- can be used in models to estimate the possible effects of COVID-19 in U.S. states and localities. (cdc.gov)
  • I develop models to estimate how large benefits could be expected for patients taking into account biological diversity and other parameters such as: how advanced the disease is, variation in health-care staff, etc. (lu.se)
  • One such example of a spiking neuron model may be a highly detailed mathematical model that includes spatial morphology. (wikipedia.org)
  • When choosing tFhe appropriate mathematical model, element type and degree of discretization are important to obtain accurate as well as time and cost effective solutions. (bvsalud.org)
  • Most importantly, it is not clear whether all the model details and the corresponding parameters are necessary for a desired set of model predictions. (tufts.edu)
  • Investigating linear, linearly interactive, and quadratic RSMs, we efficiently eliminated approximately 90% of the terms as being not highly significant, shedding light on the importance of each of the 51 original model parameters in the predictions of the metabolic model. (tufts.edu)
  • In general, generative models do better than black-box models when it comes to making inferences, but not when it comes to making essential predictions. (washingtonindependent.com)
  • know the critical assumptions of statistical models such as linear and generalized models, specifically independence and the mean-variance relationship. (uit.no)
  • know the importance of assumptions when using statistical models for the robustness of the conclusions, and the relative importance of assumptions (independence, variance-mean relationship, normality, etc. (uit.no)
  • know how to focus on the biological significance and interpretation of parameters rather than statistical significance. (uit.no)
  • Genetic interaction can be defined as a deviation of the phenotypic quantitative effect of a double gene mutation from the effect predicted from single mutations using a simple (e.g., multiplicative or linear additive) statistical model. (researchgate.net)
  • A more robust theory can be achieved by incorporating additional statistical parameters and by incorporating aspects of known biological mechanisms into the models. (usda.gov)
  • 2000. TLVs and BEIs: Threshold limit values for chemical substances and physical agents and biological exposure indices. (cdc.gov)
  • Submitted to the Dept. of Chemical and Biological Engineering. (tufts.edu)
  • Department of Chemical and Biological Engineering. (tufts.edu)
  • In contrast, such stochastic effects are taken into account by models based on the chemical master equation (CME). (biorxiv.org)
  • Models of bladder cancer incidence were evaluated taking into account possible healthy worker survivor effects. (cdc.gov)
  • A computerized epidemiological model of the spread of the mosquito-borne West Nile virus in 17 counties of California in 2005 successfully predicted where 81.6 percent of human cases of the disease would arise and defined high-risk areas where the risk of infection turned out to be 39 times higher than in low-risk areas, according to newly published research. (infectioncontroltoday.com)
  • Each scenario is based on a set of numerical values for biological and epidemiological characteristics of COVID-19 illness, which is caused by the SARS-CoV-2 virus. (cdc.gov)
  • Another may be a conductance-based neuron model that views neurons as points and describes the membrane voltage dynamics as a function of transmembrane currents. (wikipedia.org)
  • A mathematically simpler "integrate-and-fire" model significantly simplifies the description of ion channel and membrane potential dynamics (initially studied by Lapique in 1907). (wikipedia.org)
  • Often this inability comes from the fact that ODE models replace stochastic dynamics by some average. (biorxiv.org)
  • Generative Model - What Are Its Categories For Brain Dynamics Study? (washingtonindependent.com)
  • The generative model architecture class is a group of tools that are improving at recreating the dynamics of both brain parts and the brain. (washingtonindependent.com)
  • Several hybrid generative models can be used to make models of brain dynamics that can be understood. (washingtonindependent.com)
  • Beginning with a global overview, the report explores the dynamics that have a strong influence on the biological safety cabinet market and can also impact its future growth. (medgadget.com)
  • Utilizing analysis of variance (ANOVA) and response surface model (RSM) tools we develop a simplified nonlinear meta-model in which only the significant parameters are retained. (tufts.edu)
  • The tool is implemented in Java and is available for download at ftp://ftp.pcbi.upenn.edu/GMM/.CONCLUSION:Markov modeling is an important component of many sequence analysis tools. (umd.edu)
  • The proposed generalizations of the Markov model are likely to improve the overall accuracy of sequence analysis tools. (umd.edu)
  • Swot analysis of the market has also been presented in the report which highlights the strengths, weaknesses, opportunities and threats pertaining to the biological safety cabinet industry. (medgadget.com)
  • Furthermore, the value chain analysis of the biological safety cabinet industry has also been covered in the report. (medgadget.com)
  • Biological members will be involved in image acquisition and analysis of time-lapse images of cultured cells. (clarkson.edu)
  • This analysis discriminates between different biological mechanisms to achieve a transient signal from a sustained TGF-b input, where one mechanism is to use a negative feedback to turn the signal off. (lu.se)
  • Further analysis in terms of parameter sensitivity reveals that this negative feedback loop in TGF-b signaling renders the system global robustness. (lu.se)
  • It is used to simulate the Monte Carlo method, ST naturally provides ensembles of kinetics of large signaling networks, where one cannot only solutions rather than single ones, subject to analysis by rely on biological intuition. (lu.se)
  • The results obtained can then be studied using visualization software within the FEM environment to view a variety of parameters, and to fully identify implications of the analysis. (bvsalud.org)
  • Possible applications are to the development and analysis of biological neural networks. (lu.se)
  • The model parameters R ∞ , R 1 and C are estimated using the derived set of equations based on measured values of real ( R ) and imaginary part ( X ) of bioimpedance, as well as the numerical approximation of the first derivative of quotient R / X with respect to angular frequency. (nature.com)
  • Aims of neuron models Ultimately, biological neuron models aim to explain the mechanisms underlying the operation of the nervous system. (wikipedia.org)
  • These models are often run on neural networks and may learn to detect the data's inherent distinguishing qualities. (washingtonindependent.com)
  • Elisabetta Chicca has more than 20 years experience in the field of neuromorphic engineering and neural networks modeling. (lu.se)
  • In this study, a meshless radial point interpolation method is applied to demonstrate the elastic response of rubber-like materials based on the Mooney- Rivlin model. (easychair.org)
  • This study uses simple illustrative examples to demonstrate how inconsistent parameter estimates may result from an algorithm that is considered fast and precise. (ices.dk)
  • Non-spiking cells, spiking cells, and their measurement Not all the cells of the nervous system produce the type of spike that define the scope of the spiking neuron models. (wikipedia.org)
  • Serious' effects are those that evoke failure in a biological system and can lead to morbidity or mortality (e.g., acute respiratory distress or death). (cdc.gov)
  • In this context, a biological system can be seen as a complex network composed of different functional parts (14) . (igem.org)
  • In order to achieve this task, we will consider three different models: the first one shows the basal property we are looking for: a system able to produce glue. (igem.org)
  • We start from the global biological system established in the first section (cf. (igem.org)
  • In this first step, we present a simplified model of our system. (igem.org)
  • In this first model we consider only the situation with IPTG inside the system: β ≠ 0. (igem.org)
  • By solving this system of equations for the previous set of parameters we can find different sets of stationary states. (igem.org)
  • New failure model for determination of failure rates of system components in accordance with system state is introduced. (wseas.org)
  • Instead, we need to capture the key parameters for the target system which are necessary to explain the process we are interested in. (helsinki.fi)
  • The system was evaluated and characterized regarding the effect of temperature on growth and product formation, as represented by efficiency parameters and yields. (springer.com)
  • Biological neuron models, also known as a spiking neuron models, are mathematical descriptions of neurons. (wikipedia.org)
  • Overview of neuron models Neuron models can be divided into two categories according to the physical units of the interface of the model. (wikipedia.org)
  • Natural stimulus or pharmacological input neuron models - The models in this category connect between the input stimulus which can be either pharmacological or natural, to the probability of a spike event. (wikipedia.org)
  • Although it is not unusual in science and engineering to have several descriptive models for different abstraction/detail levels, the number of different, sometimes contradicting, biological neuron models is exceptionally high. (wikipedia.org)
  • Though these issues are central to modelling in fisheries science, discussion on them has been limited to scientists with a strongly quantitative background. (ices.dk)
  • Parameters were then fit to a nonlinear anisotropic constitutive equation, for aortic sinus and aortic wall. (actapress.com)
  • First, we investigated the sensitivity of the method to experimental noise and to initial parameter values. (actapress.com)
  • There have been many in silico studies based on a Boolean network model to investigate network sensitivity against gene or interaction mutations. (researchgate.net)
  • These beneficial biological properties have been extensively studied in humans and animal models, both in vitro and in vivo . (hindawi.com)
  • Several reports in the literature have focussed on the formulation of the modelling approach applied to highly idealized arterial and stent geometries. (springer.com)
  • Protein-protein interaction models have been used to study the solution structure of 5 MAbs and their protein-protein interactions at high concentrations under specific formulation conditions where they remain soluble. (lu.se)
  • However, most current forecasting approaches do not incorporate species-specific, process-based biological information, which limits their ability to inform actionable strategies. (frontiersin.org)
  • One of the things that really differentiates DYCAST from other approaches is that its based on biological parameters,' says Ryan Carney, a Brown University graduate student who is the lead author on a paper about DYCASTs performance that appears in the current issue of the journal Emerging Infectious Diseases, published by the Centers for Disease Control and Prevention (CDC). (infectioncontroltoday.com)
  • Adjustment of OELs on the basis of differences in modeling approaches to derive BCFs when setting OELs. (cdc.gov)
  • We use the proposed method to gain insight into the nature of asynchronous vs. synchronous updating in Boolean models and successfully simulate a 41 species apoptosis model on a standard desktop workstation. (biorxiv.org)
  • However, especially for Boolean models (for details see below) this essentially assumes that a large number of species is either on or off with probability 1, a very unrealistic assumption. (biorxiv.org)
  • A procedure (algorithm) is considered efficient when it is stable (i.e., given the same input information, it returns identical estimates of parameters), fast, and precise. (ices.dk)
  • Refitting the 6 highly significant terms yields a 55% improvement in the objective function from the original model fitting, as compared to refitting the 12 highly insignificant terms which results in just a 6% improvement in the objective function. (tufts.edu)
  • It was also found that some biological parameters, such as asymptotic threshold shift and pre-exposure DPOAE did not contribute much to increasing the prediction accuracy (in many cases these variables made the prediction results worse). (cdc.gov)
  • A conceptual model was constructed for the functioning the algae-dominated rocky reef ecosystem of the Mediterranean Sea. (csic.es)
  • Models based on ordinary differential equations (ODE) are most commonly used [ 12 ]. (biorxiv.org)
  • Models are also important in the context of restoring lost brain functionality through neuroprosthetic devices. (wikipedia.org)
  • The report also analyses the competitive structure of the biological safety cabinet industry and provides the profiles of major players operating in the market. (medgadget.com)
  • Moreover, in order to determine market attractiveness, the report analyses the biological safety cabinet industry along the parameters of the porter's five forces model. (medgadget.com)
  • This model, comprising 51 parameters and 34 reaction fluxes, was able to provide a reliable preliminary prediction of the effects of fed-batch process variables such as temperature shift, specific productivity, and nutrient concentrations. (tufts.edu)
  • S(0)s determined using SAXS and SLS for the different MAbs are then compared, based on the individual isoelectric point and net charge distribution over the surface for each MAb, to gain a deeper understanding of how these parameters affect protein-protein interactions at high concentrations. (lu.se)
  • The evaluation was done on four classes of biological sequences - CpG-poor promoters, all promoters, exons and nucleosome positioning sequences. (umd.edu)
  • While much research is, and has been, carried out to investigate the effects of hypoxia, this is usually done using experimental models which employ stable levels of hypoxia. (mdpi.com)
  • For long term complex noise exposures 10 noise metrics and 5 biological parameters were used as the inputs of the prediction model in the initial stage of the research project. (cdc.gov)
  • Carney said that by using biology to define the geographic and temporal attributes of the model rather than county or census tract borders, which are convenient for humans but irrelevant to birds and mosquitoes, the model allowed the California Department of Public Health to provide early warnings to an area stretching from the Bay Area through Sacramento to the Nevada line, as well as regions in southern California. (infectioncontroltoday.com)
  • To that end, we will monitor the synaptic alterations over time in controls as well as in defined models with the aim to better define synaptic aging and to identify druggable targets involved in the loss of synapses and neurons. (uni-ulm.de)
  • These equations are expressed in terms of unknown variables (parameters) that collectively define the model parameter set. (ices.dk)
  • For impulse noise exposures parameters, such as peak, duration, number and rate, are important to the prediction of NIHL. (cdc.gov)
  • In addition, we suggest several computational tools for studying the distribution of double mutants in the space of model phenotype probabilities. (researchgate.net)
  • Neo - Hookean is a material model for hyperelastic solid which contains only two material parameters: bulk modulus and shear modulus. (easychair.org)
  • We extract intrinsic layered material parameters of the articular cartilage using a triphasic model. (who.int)
  • Synthetic biology is a recent development in biology which aims at producing useful material via biological agents. (igem.org)
  • For example, the spatial parameters of the model include how far mosquitoes and infected birds are likely to fly. (infectioncontroltoday.com)
  • Each category could be further divided according to the abstraction/detail level: Electrical input-output membrane voltage models - These models produce a prediction for membrane output voltage as a function of electrical stimulation given as current or voltage input. (wikipedia.org)
  • After 2005, the department implemented the model throughout the state, although the number of human cases and reported dead birds, along with the models prediction rates, dropped sharply. (infectioncontroltoday.com)
  • Both noise metrics and biological parameters were used as input variables to the prediction models. (cdc.gov)
  • Since the prediction models consist of individual biological information, it should be possible to predict noise -induced hearing loss in an individual. (cdc.gov)
  • Two frequency specific prediction models were considered: One was a specific frequency model (SF model), the other was a wide band frequency model (WF model). (cdc.gov)
  • In the SF model a prediction model was built for each specified frequency. (cdc.gov)
  • In the WF prediction model contiguous frequency band information on either upper or lower side(s) of a specified frequency band were considered as additional input(s) for the models. (cdc.gov)
  • The prediction models using partition 1 and 2 were built and tested. (cdc.gov)
  • It was found that the prediction models using the WF method would yield the best average prediction accuracy. (cdc.gov)
  • The RBF model with the SF method was selected as the best prediction model. (cdc.gov)
  • The effects of electromagnetic fields on living organs have been explored with the use of both biological experimentation and computer simulations. (intechopen.com)
  • Hands on Computers: Introduction to igraph and Network Modelling: Presentation of the package igraph. (bio.net)
  • The next step of our mathematical design is the modeling of the interactions between all the different blocks. (igem.org)
  • Such models aim to predict cellular response to various external stimuli, allowing an investigator to develop a detailed fundamental understanding of the phenomena studied. (tufts.edu)
  • and taking into account the spatiality of the biological phenomena. (ens-lyon.fr)
  • A slightly different model was used to quantify the role that fast diagnosis and efficient isolation of patients played in Toronto's outbreak ( 10 ). (cdc.gov)
  • This document was first posted on May 20, 2020, with the understanding that the parameter values in each scenario would be updated and augmented over time, as we learn more about the epidemiology of COVID-19. (cdc.gov)
  • Scenarios 1 through 4 are based on parameter values that represent the lower and upper bounds of disease severity and viral transmissibility (moderate to very high severity and transmissibility). (cdc.gov)
  • Parameters values result from the literature and previous iGEM team wiki's. (igem.org)
  • Running the model for the different values of R0, we quantified the number of symptomatic clinical cases, the clinical attack rates, the symptomatic clinical attack rates and the number of deaths. (who.int)
  • The model fit to the measured particle mass by organ was very good for the lungs, brain, and spleen (R2=0.81-0.98) in both studies, but not as good for the liver and kidney (R2=0.32-0.53). (cdc.gov)
  • Participation in the calibration of the model parts dealing with above studies. (vliz.be)
  • For each of these regions, the report studies the biological safety cabinet market in detail for latest trends, outlook and opportunities. (medgadget.com)
  • Different test parameters and standards are used in the experimental studies, which might be the cause of the controversy surrounding the issue of fracture resistance of teeth restored with endodontic posts. (bvsalud.org)