Titlebook: Computational Modeling of Signaling Networks; Xuedong Liu,Meredith D. Betterton Book 2012 Springer Science+Business Media, LLC 2012 BioNet

民俗學(xué)

書(shū)目名稱(chēng)Computational Modeling of Signaling Networks影響因子(影響力)




書(shū)目名稱(chēng)Computational Modeling of Signaling Networks影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Computational Modeling of Signaling Networks網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Computational Modeling of Signaling Networks網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Computational Modeling of Signaling Networks被引頻次




書(shū)目名稱(chēng)Computational Modeling of Signaling Networks被引頻次學(xué)科排名




書(shū)目名稱(chēng)Computational Modeling of Signaling Networks年度引用




書(shū)目名稱(chēng)Computational Modeling of Signaling Networks年度引用學(xué)科排名




書(shū)目名稱(chēng)Computational Modeling of Signaling Networks讀者反饋




書(shū)目名稱(chēng)Computational Modeling of Signaling Networks讀者反饋學(xué)科排名

manifestation

Some Mathematical Aspects of Buckling,y depends in a highly nonlinear fashion on its parameters and, as a consequence, parameter estimation procedures get easily trapped in local optima. Therefore any useful parameter estimation procedure has to be robust and efficient with respect to both challenges. In the final step, it is important

離開(kāi)真充足

https://doi.org/10.1007/978-94-009-3373-6 The model was used not only to investigate different possible designs of the silencing mechanism exerted by miR-34a on Sirt1 but also to simulate the dynamics of the system under conditions of (pathological) deregulation of its compounds.

情節(jié)劇

G. Thomas,H. J. Prijs,J. J. Trapman possible. These languages are also intuitive to the biologist and accessible to the novice modeler. In this chapter, we provide a self-contained tutorial on modeling signal transduction networks using the BNG Language and related software tools. We review the basic syntax of the language and show h

放逐

Analyzing and Constraining Signaling Networks: Parameter Estimation for the User,y depends in a highly nonlinear fashion on its parameters and, as a consequence, parameter estimation procedures get easily trapped in local optima. Therefore any useful parameter estimation procedure has to be robust and efficient with respect to both challenges. In the final step, it is important

完成

完成

攤位

征兵

Predictive Models for Cellular Signaling Networks,m attractors of dynamic systems. We then discuss the use of bifurcation diagrams to evaluate the parameter dependency of qualitative network behaviors (i.e., the emergence of oscillations or switches), and we give measures for the sensitivity and robustness of the signaling output.

哺乳動(dòng)物

A Tutorial on Mathematical Modeling of Biological Signaling Pathways,f the network components and employs mathematical models to gain some insights about the mechanisms and dynamics of biological systems. This chapter introduces how to use the bottom-up approach to establish mathematical models for cell signaling studies.