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Related Concept Videos

Mathematical Modeling: Problem Solving01:29

Mathematical Modeling: Problem Solving

Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
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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...
Skin Cancer01:30

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Skin cancer is a type of cancer that occurs when there is an abnormal growth of skin cells, usually triggered by damage to the DNA within the skin cells. It is primarily caused by exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds. Skin cancer is the most common type of cancer worldwide, and its incidence continues to rise.
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Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs01:21

Fundamental Mathematical Principles in Pharmacokinetics: Calculus and Graphs

The fundamental mathematical principles, such as calculus and graphs, play crucial roles in analyzing drug movement and determining pharmacokinetic parameters. Differential calculus examines rates of change and helps to determine the dissolution rate of drugs in biofluids, as well as how drug concentrations change over time. For instance, it can help calculate the rate of elimination of a drug from the body based on its concentration-time profile.
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Related Experiment Video

Updated: May 13, 2026

Whole-mount Confocal Microscopy for Adult Ear Skin: A Model System to Study Neuro-vascular Branching Morphogenesis and Immune Cell Distribution
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Whole-mount Confocal Microscopy for Adult Ear Skin: A Model System to Study Neuro-vascular Branching Morphogenesis and Immune Cell Distribution

Published on: March 29, 2018

Skin disease modeling from a mathematical perspective.

Reiko J Tanaka1, Masahiro Ono

  • 1Department of Bioengineering, Imperial College London, London, UK. r.tanaka@imperial.ac.uk

The Journal of Investigative Dermatology
|March 22, 2013
PubMed
Summary
This summary is machine-generated.

Mathematical modeling offers insights into skin disease mechanisms. Integrating experiments, data analysis, and modeling is crucial for advancing dermatology research in the postgenomic era.

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Area of Science:

  • Dermatology
  • Computational Biology
  • Systems Biology

Background:

  • Mathematical modeling is an emerging technique for understanding complex biological systems.
  • Skin diseases involve intricate regulatory networks that are challenging to elucidate through traditional methods.

Purpose of the Study:

  • To provide an overview of mathematical modeling applications in skin disease research.
  • To highlight the benefits and challenges associated with mathematical modeling in dermatology.
  • To emphasize the need for interdisciplinary collaboration in skin research.

Main Methods:

  • Review of current literature on mathematical modeling in skin biology.
  • Discussion of the integration of experimental data, computational modeling, and statistical analysis.
  • Exploration of the role of postgenomic data in driving modeling approaches.

Main Results:

  • Mathematical modeling can reveal disease-related regulatory mechanisms in the skin.
  • Successful application requires strong links between experimental findings and computational analysis.
  • The postgenomic era necessitates advanced analytical tools like mathematical modeling.

Conclusions:

  • Mathematical modeling is a valuable tool for advancing skin disease understanding.
  • Effective utilization demands a synergistic approach combining experimentation, data analysis, and modeling.
  • Investigative dermatologists are essential to guide this cross-disciplinary field toward fundamental discoveries.