细胞技术

The growth inhibition of dividing cells and most of the transcriptional responses upon TGF-β treatment depend on the Smad2, Smad3, and Smad4 transcription factors. These proteins shuttle continuously between the cytoplasm and the nucleus, transmitting the ligand status of the TGF-β re ...

Nuclear microenvironments are architecturally organized subnuclear sites where the regulatory machinery for gene expression, replication, and repair resides. This compartmentalization is necessary to attain required stoichiometry for organization and assembly of ...

Adrenal corticosteroids (cortisol in humans/corticosterone in rodents) readily enter the brain and exert markedly diverse effects, such as the stress response of target neural cells. These effects are regulated via two receptor systems, the mineralocorticoid receptor (MR) and the ...

β-Catenin is a multifunctional protein which is overexpressed in several types of cancers. The subcellular location of β-catenin at the membrane junctions or in the nucleus determines its function in cell adhesion and transcription activation, respectively. The aberrant localiz ...

Post-translational modifications and subcellular localizations modulate transcription factors, generating a code that is deciphered into an activity. We describe our current understanding of these processes for Ets factors, which have recently been recognized for their im ...

Regulation of protein degradation is an important mechanism by which concentrations of proteins is controlled in cells. In addition to proteins involved in cell cycle regulation or mitosis, protein levels of many transcription factors are regulated by targeted proteosomal degrad ...

Human exposures to environmental toxicants have been associated with etiology of many diseases including inflammation, cancer, and cardiovascular and neurodegenerative disorders. To counteract the detrimental effect of environmental insults, mammalian cells have evo ...

Transcription factor proteins function in the nucleus to regulate gene expression. Many transcription factors are critical regulators of tumor progression. Conversely, many oncogenic and tumor suppressor proteins are transcription factors or other types of nuclear protei ...

The program PottersWheel has been developed to provide an intuitive and yet powerful framework for data-based modeling of dynamical systems like biochemical reaction networks. Its key functionality is multi-experiment fitting, where several experimental data sets from diffe ...

This chapter describes approaches to make use of dynamic models of cell signaling systems in order to optimize experiments in cell biology. We are particularly focusing on the question of how small molecule inhibitors or activators can best be used to get the most information out of a limited numb ...

MicroRNAs (miRNAs) are a family of small regulatory RNAs whose function is to regulate the activity and stability of specific messenger RNA targets through posttranscriptional regulatory mechanisms. Most of the times signaling systems involving miRNA modulation are not linear pa ...

We have used a mathematical model of the Ras signaling network to link observable biochemical properties with cellular levels of RasGTP. Although there is abundant data characterizing Ras biochemistry, attributing specific changes in biochemical properties to observed phenot ...

When several genes or proteins modulate one another’s activity as part of a network, they sometimes produce behaviors that no protein could accomplish on its own. Intuition for these emergent behaviors often cannot be obtained simply by tracing causality through the network in discreet st ...

Mathematical models have been widely used in the studies of biological signaling pathways. Among these studies, two systems biology approaches have been applied: top-down and bottom-up systems biology. The former approach focuses on X-omics researches involving the measurement of ...

The behavior of most dynamical models not only depends on the wiring but also on the kind and strength of interactions which are reflected in the parameter values of the model. The predictive value of mathematical models therefore critically hinges on the quality of the parameter estimates. Con ...

This chapter provides an introduction to the formulation and analysis of differential-equation-based models for biological regulatory networks. In the first part, we discuss basic reaction types and the use of mass action kinetics and of simplifying approximations in the developm ...

Recent single-cell experiments have revived interest in the unavoidable or intrinsic noise in biochemical and genetic networks arising from the small number of molecules of the participating species. That is, rather than modeling regulatory networks in terms of the deterministic d ...

Newly available experimental data characterizing different processes involved in signaling pathways have provided the opportunity for network analysis and modeling of these interacting pathways. Current approaches in studying the dynamics of signaling networks fall in ...

Quantitative modeling of spatiotemporal dynamics of cells facilitates understanding and engineering of biological systems. Using a synthetic bacterial ecosystem as a workbench, we present the approach to mathematically simulate the spatiotemporal population dynamics ...

We give a pedagogical introduction to computational modeling of signal transduction networks, starting from explaining the representations of chemical reactions by differential equations via the law of mass action. We discuss elementary biochemical reactions such as Michae ...