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関連する概念動画

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...
The Two-State Receptor Model01:29

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.
The binding affinity of a drug determines its interaction with one...
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

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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Updated: Jun 8, 2026

In Vitro Reconstitution of Self-Organizing Protein Patterns on Supported Lipid Bilayers
08:10

In Vitro Reconstitution of Self-Organizing Protein Patterns on Supported Lipid Bilayers

Published on: July 28, 2018

生物学的パターン形成を理解するための枠組みとして,反応-拡散モデル.

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
まとめ
この要約は機械生成です。

チューリングモデルは,動物胚における自己調節型パターンの形成を説明する. このレビューは,反応拡散 (RD) 理論と発達生物学における実験的応用について詳細に説明します.

さらに関連する動画

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior
10:07

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Published on: January 31, 2020

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy
15:13

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Published on: July 25, 2014

関連する実験動画

Last Updated: Jun 8, 2026

In Vitro Reconstitution of Self-Organizing Protein Patterns on Supported Lipid Bilayers
08:10

In Vitro Reconstitution of Self-Organizing Protein Patterns on Supported Lipid Bilayers

Published on: July 28, 2018

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior
10:07

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

Published on: January 31, 2020

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy
15:13

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Published on: July 25, 2014

科学分野:

  • 発達生物学 発達生物学について
  • 理論生物学理論生物学について
  • 数学生物学数学生物学について

背景:

  • 反応拡散理論 (RD) とも呼ばれるチューリングモデルは,自己組織化パターン形成を理解するための基本的概念です.
  • 歴史的に見て,このモデルの生物学的システムへの直接的適用性は懐疑的であった.
  • 最近の説得力のある事例は,開発プロセスにおけるR&Dモデルの関連性をますます検証しています.

研究 の 目的:

  • 実験生物学者のためのチューリング (RD) モデルの基本原理を解明する.
  • RDモデルが,様々な形態学的研究における作業仮説としてどのように役立つかを示します.
  • パターン形成におけるR&Dモデルの適用を支持する実験的証拠をレビューする.

主な方法:

  • 反応拡散システムの理論的基礎のレビュー.
  • RDモデルのパターン生成のための数学的要件の分析.
  • RDモデルの応用を実証する実験的ケーススタディのまとめと議論.

主要な成果:

  • RDモデルは,多様な空間パターンを生成することができます.
  • 数学的分析は,異なるパターン型に必要とされる特定の相互作用を明確にします.
  • 実験的研究は,生物学的パターン形成における RD モデルの役割の具体的な証拠を提供します.

結論:

  • チューリング (RD) モデルは,生物学的パターン形成を理解するための強力な理論的枠組みです.
  • モデルの現実世界の関連性に関する懐疑論は,経験的証拠によって著しく減少しています.
  • RDモデルは,発達生物学における形態学的現象を調査するための貴重な仮説生成ツールを提供します.