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相关概念视频

Modeling with Differential Equations01:25

Modeling with Differential Equations

Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
Diffusion01:12

Diffusion

Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
Transition State Theory01:25

Transition State Theory

Transition-state theory, also known as activated-complex theory, provides a molecular-level explanation of reaction rates in both gas-phase and solution-phase reactions. It extends earlier kinetic models by considering the formation of a short-lived, high-energy configuration during a reaction.The progress of a chemical reaction can be represented using a reaction profile, which plots potential energy against the reaction coordinate. As two reactant molecules approach one another, their...
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The Two-State Receptor Model

The two-state receptor model explains a drug's interaction with receptors, such as G protein-coupled receptors and ligand-gated ion channels, to induce or inhibit a biological response. When no natural ligands are present, a receptor exists in an equilibrium of inactive (Ri) and active (Ra) conformations. The inactive form does not produce a response, while the active form generates a basal effect known as constitutive activity.
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Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...

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In Vitro Reconstitution of Self-Organizing Protein Patterns on Supported Lipid Bilayers
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反应-扩散模型作为理解生物模式形成的框架.

Shigeru Kondo1, Takashi Miura

  • 1Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka, 565-0871, Japan. skondo@fbs.osaka-u.ac.jp

Science (New York, N.Y.)
|October 9, 2010
PubMed
概括
此摘要是机器生成的。

图灵模型解释了动物胚胎中自我调节的模式形成. 本综述详细介绍了反应扩散 (RD) 理论及其在发育生物学中的实验应用.

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Last Updated: Jun 8, 2026

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08:10

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Published on: July 28, 2018

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科学领域:

  • 发展生物学 发展生物学
  • 理论生物学 理论生物学
  • 数学生物学 数学生物学

背景情况:

  • 图灵模型,也称为反应扩散 (RD) 理论,是理解自我组织模式形成的基础概念.
  • 从历史上看,该模型对生物系统的直接适用性面临怀疑.
  • 最近令人信服的例子越来越多地验证了 RD 模型在发展过程中的相关性.

研究的目的:

  • 为实验生物学家阐明图灵 (RD) 模型的核心原则.
  • 展示 RD 模型如何在各种形态学研究中作为工作假设.
  • 审查支持RD模型在模式形成中的应用的实验证据.

主要方法:

  • 审查反应扩散系统的理论基础.
  • 在RD模型中分析模式生成的数学要求.
  • 汇编和讨论实验案例研究,展示RD模型的应用.

主要成果:

  • 该RD模型能够生成多样化的空间模式.
  • 数学分析澄清了不同模式类型所需的特定相互作用.
  • 实验研究提供了 RD 模型在生物模式形成中的作用的具体证据.

结论:

  • 图灵模型 (RD) 是一个强大的理论框架,用于理解生物模式形成.
  • 对该模型在现实世界的相关性持怀疑态度,经验证据显著减少.
  • RD模型为研究发育生物学中的形态现象提供了一个有价值的假设生成工具.