转变 发表于 2025-3-21 17:27:36

书目名称Cell Movement影响因子(影响力)<br>        http://impactfactor.cn/2024/if/?ISSN=BK0222855<br><br>        <br><br>书目名称Cell Movement影响因子(影响力)学科排名<br>        http://impactfactor.cn/2024/ifr/?ISSN=BK0222855<br><br>        <br><br>书目名称Cell Movement网络公开度<br>        http://impactfactor.cn/2024/at/?ISSN=BK0222855<br><br>        <br><br>书目名称Cell Movement网络公开度学科排名<br>        http://impactfactor.cn/2024/atr/?ISSN=BK0222855<br><br>        <br><br>书目名称Cell Movement被引频次<br>        http://impactfactor.cn/2024/tc/?ISSN=BK0222855<br><br>        <br><br>书目名称Cell Movement被引频次学科排名<br>        http://impactfactor.cn/2024/tcr/?ISSN=BK0222855<br><br>        <br><br>书目名称Cell Movement年度引用<br>        http://impactfactor.cn/2024/ii/?ISSN=BK0222855<br><br>        <br><br>书目名称Cell Movement年度引用学科排名<br>        http://impactfactor.cn/2024/iir/?ISSN=BK0222855<br><br>        <br><br>书目名称Cell Movement读者反馈<br>        http://impactfactor.cn/2024/5y/?ISSN=BK0222855<br><br>        <br><br>书目名称Cell Movement读者反馈学科排名<br>        http://impactfactor.cn/2024/5yr/?ISSN=BK0222855<br><br>        <br><br>

要塞 发表于 2025-3-21 22:17:36

The Role of Microenvironment in Regulation of Cell Infiltration in Glioblastoma, with microglia and macrophages which are recruited by tumor cells to facilitate growth and invasion. In this study we investigate the biochemical and cell-mechanical interactions between the glioma cells and the microenvironment including resident glial cells and M1/M2 microglia that enhance tumor

Suppository 发表于 2025-3-22 01:56:33

A Multiscale Model of Cell Migration in Three-Dimensional Extracellular Matrix,answered. In this chapter, we introduce a modeling framework for a 3D, element-based, multiscale cell migration model. This model takes into account the mechanosensing signaling pathway, cell morphological dynamics, and cell-ECM interactions. To integrate the mechanochemical dynamics, we developed a

Axon895 发表于 2025-3-22 05:26:12

Bayesian Uncertainty Quantification for Particle-Based Simulation of Lipid Bilayer Membranes,A recent approach to Bayesian uncertainty quantification using transitional Markov chain Monte Carlo (TMCMC) is extremely parallelizable and has opened the door to a variety of applications which were previously too computationally intensive to be practical. In this chapter, we first explore the mac

上坡 发表于 2025-3-22 11:07:00

From Random Walks to Fully Anisotropic Diffusion Models for Cell and Animal Movement,w the availability of measurement data can guide the choice of the appropriate model. We further present two new applications, respectively to cell movement on micro-fabricated surfaces and magnetic compass orientation by sea turtle hatchlings.

CLOUT 发表于 2025-3-22 16:10:47

Bacterial Chemotaxis: A Classic Example of Multiscale Modeling in Biology,sed models can faithfully replicate the detailed mechanisms of cell signaling and movement but are computationally intensive. PDE models are amenable for fast computation and mathematical analysis but are often based on phenomenological descriptions of macroscopic cell fluxes. Multiscale methods mus

CLOUT 发表于 2025-3-22 19:56:15

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maverick 发表于 2025-3-22 23:57:36

Lamellipodia in Stationary and Fluctuating States,cells. These models are motivated by experimental results using cells with flat, steady lamellipodia studied by Single Molecule Speckle microscopy. The same cells can also be made to exhibit protruding and retracting lamellipodia, which demonstrate how changes in actin polymerization lead to changes

BRAND 发表于 2025-3-23 01:24:58

Intracellular Membrane Trafficking: Modeling Local Movements in Cells,s a broad range of biological processes, all of which are characterized by the local deformation and movement of the plasma membrane. These movements are orchestrated by a complex protein machinery and cytoskeletal rearrangements. While different membrane trafficking pathways use different sets of p

Infinitesimal 发表于 2025-3-23 08:30:51

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查看完整版本: Titlebook: Cell Movement; Modeling and Applica Magdalena Stolarska,Nicoleta Tarfulea Book 2018 Springer Nature Switzerland AG 2018 Bayesian Uncertaint