Optimization of Nonlinear Dose- and Concentration-Response Models Utilizing Evolutionary Computation

Beam, Andrew L.; Motsinger-Reif, Alison A.
July 2011
Dose-Response;2011, Vol. 9 Issue 3, p387
Academic Journal
An essential part of toxicity and chemical screening is assessing the concentrated related effects of a test article. Most often this concentration-response is a nonlinear, necessitating sophisticated regression methodologies. The parameters derived from curve fitting are essential in determining a test article's potency (EC50) and efficacy (Emax) and variations in model fit may lead to different conclusions about an article's performance and safety. Previous approaches have leveraged advanced statistical and mathematical techniques to implement nonlinear least squares (NLS) for obtaining the parameters defining such a curve. These approaches, while mathematically rigorous, suffer from initial value sensitivity, computational intensity, and rely on complex and intricate computational and numerical techniques. However if there is a known mathematical model that can reliably predict the data, then nonlinear regression may be equally viewed as parameter optimization. In this context, one may utilize proven techniques from machine learning, such as evolutionary algorithms, which are robust, powerful, and require far less computational framework to optimize the defining parameters. In the current study we present a new method that uses such techniques, Evolutionary Algorithm Dose Response Modeling (EADRM), and demonstrate its effectiveness compared to more conventional methods on both real and simulated data.


Related Articles

  • Effective Structure Learning for Estimation of Distribution Algorithms via L1-Regularized Bayesian Networks. Hua Xu; Jiadong Yang; Peifa Jia; Yi Ding // International Journal of Advanced Robotic Systems;Jan2013, Vol. 10, p1 

    Estimation of distribution algorithms (EDAs), as an extension of genetic algorithms, samples new solutions from the probabilistic model, which characterizes the distribution of promising solutions in the search space at each generation. This paper introduces and evaluates a novel estimation of a...

  • Moderate deviations for M-estimators in linear models with Ï•-mixing errors. Fan, Jun // Acta Mathematica Sinica;Jun2012, Vol. 28 Issue 6, p1275 

    In this paper, the moderate deviations for the M-estimators of regression parameter in a linear model are obtained when the errors form a strictly stationary Ï•-mixing sequence. The results are applied to study many different types of M-estimators such as Huber's estimator, L-regression...

  • New ridge parameters for ridge regression. Dorugade, A. V. // Journal of the Association of Arab Universities for Basic & Appl;Apr2014, Vol. 15 Issue 1, p94 

    Hoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the ordinary least squares (OLS) estimator in the presence of multicollinearity. In ridge regression, ridge parameter plays an important role in parameter estimation. In this article, a new method for...

  • A New Algorithm for Detecting Outliers in Linear Regression. Satman, Mehmet Hakan // International Journal of Statistics & Probability;Aug2013, Vol. 2 Issue 3, p101 

    In this paper, we present a new algorithm for detecting multiple outliers in linear regression. The algorithm is based on a non-iterative robust covariance matrix and concentration steps used in LTS estimation. A robust covariance matrix is constructed to calculate Mahalanobis distances of...

  • Combine Estimate of Regression Coefficients. Shiqing Wang; Xiaohua Li // Advances in Information Sciences & Service Sciences;Nov2012, Vol. 4 Issue 21, p533 

    For linear regression models which have the problem of multicollinearity, the ordinary least squares estimate is not a good estimate of regression coefficients. So many have been done to circumvent this problem, one of them is proposing some biased estimate. In the paper, based on the least...

  • Optimal experiment design for thermal diffusivity estimation of bi-layered materials. FAOUEL, JIHENE; MZALI, FOUED; JEMNI, ABDELMAJID; NASRALLAH, SASSI BEN // High Temperatures -- High Pressures;2010, Vol. 39 Issue 2, p113 

    This paper presents a novel method for a simultaneous thermal diffusivity estimation of both isotropic layers of a bi-layered composite using a photo-thermal technique. This consists on exposing the bi-layered material on a part of its front face to an irradiation heat flux and recording the...

  • An Optimal Control Model and the Computer Algorithm for the Diffusion Parameter of the Drug Releasing in the Spherical Device. Li, Y.; Dong, M.; Xiang, X.; Xiang, Z.; Pang, Y. // Information Technology Journal;2012, Vol. 11 Issue 8, p1032 

    In this study, we established an optimization control model and the corresponding computer algorithm to estimate the diffusion coefficient of the drug releasing in the spherical device. First, based on the diffusion equation in the spherical device in the polar coordinates system, the optimal...

  • Parameter and State Estimation Algorithm for a State Space Model with a One-unit State Delay. Gu, Ya; Lu, Xianling; Ding, Ruifeng // Circuits, Systems & Signal Processing;Oct2013, Vol. 32 Issue 5, p2267 

    This paper derives a state estimation based parameter identification algorithm for state space systems with a one-unit state delay. We derive the identification model of an observability canonical state space system with a one-unit state delay. The key is to replace the unknown states in the...

  • Automatic Variogram Modeling by Iterative Least Squares: Univariate and Multivariate Cases. Desassis, N.; Renard, D. // Mathematical Geosciences;May2013, Vol. 45 Issue 4, p453 

    In this paper, we propose a new methodology to automatically find a model that fits on an experimental variogram. Starting with a linear combination of some basic authorized structures (for instance, spherical and exponential), a numerical algorithm is used to compute the parameters, which...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics