The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In recent years, targeted therapy to treat cancer is gaining popularity. However, how to quantitatively and dynamically analyze the drug effect for molecularly targeted agents is quite different from traditional cytotoxic drugs. A novel preclinical model combining experimental methods and theoretical analysis is proposed to investigate the mechanisms of action and identify pharmacodynamic characteristic...
A novel preclinical model combining experimental methods and theoretical analysis is proposed to investigate the mechanism of action and identify pharmacodynamic characteristic of a drug. Instead of fixed time point analysis of the drug exposure to drug effect, the time course of drug effect for different doses are quantitatively studied on cell line-based platforms using Kalman filter, where tumor...
In wideband cognitive radio (CR) networks, spectrum sensing is one of the key issues that enable the whole network functionality. Collaborative spectrum sensing among the cognitive radio nodes can greatly improve the sensing performance, and is also able to obtain the location information of primary radios (PRs). Most existing work merely studies the cognitive radio networks with static PRs, yet how...
A key issue in genomic signal processing is the inference of gene regulatory networks. These are used both to understand the role of biological regulation in phenotypic determination and to derive therapeutic strategies for genetic-based diseases. In this paper, gene regulatory networks are inferred via evolutionary modeling based on time-series microarray measurements. A nonlinear differential equation...
In this paper, the problem of genetic regulatory network inference from time series microarray experiment data is considered. A noisy sigmoidal model is proposed to include both system noise and measurement noise. In order to solve this nonlinear identification problem (with noise), a joint genetic algorithm and Kalman filtering approach is proposed. Genetic algorithm is applied to minimize the fitness...
In this paper, gene regulatory networks are infered through evolutionary modeling and time-series microarray measurements. A nonlinear differential equation model is adopted and an iterative algorithm is proposed to identify the model, where genetic programming is applied to identify the structure of the model and Kalman filtering is employed to estimate the parameters in each iteration. Simulation...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.