How Do You Use Applied Math as a Theoretical Tool in Biology?

In summary: The article "Mathematical Physiology: A Review" by Peskin is a good starting point for learning about the application of math in biology, specifically in the case of the sinoatrial node. In summary, to use applied math as a theoretical tool, you should have a strong foundation in mathematics and familiarize yourself with the subject and its theories through research and learning resources.
  • #1
vicsmithvic
3
0
How do you learn how to use applied math not only as a modeling tool/statistics tool/numerical analysis tool, etc., but as a theoretical tool? How do you know when a proof holds true in applied math/physics/biology? For example:

http://www.nature.com/nature/journal/v410/n6825/full/410268a0.html

This thread began with Peskin's model of the sinoatrial node, the heart's natural pacemaker, as a collection of N identical integrate-and-fire oscillators38. For the simple case where each oscillator is connected to all the others, Peskin conjectured that they would all end up firing in unison, no matter how they started. He gave a proof for N = 2 oscillators; it was later demonstrated39 that the conjecture holds for all N. Peskin also conjectured that synchronization would occur even if the oscillators were not quite identical, but that problem remains unproven.

From what I'm getting at, you basically have a really good mathematical model or law, and you are able to rephrase simple and inherently mathematical relationships in nature in terms of mathematical language. All I've seen from mathematical biology so far are differential equation models that were found long ago in physics, or geometry/topology being applied to molecules. I think I'm misunderstanding something about this topic.
 
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  • #2
In order to learn how to use applied math as a theoretical tool, you should start by studying the basics of mathematics, such as calculus, linear algebra, and probability theory. This will give you the necessary background knowledge to understand more advanced mathematical concepts. When it comes to understanding when a proof holds true in applied math/physics/biology, you should familiarize yourself with the subject and its related theories. You should also look for relevant research papers and books to gain an understanding of the current state of the field. Additionally, you can look for tutorials, online courses, and other learning resources to supplement your understanding.
 

FAQ: How Do You Use Applied Math as a Theoretical Tool in Biology?

What is theoretical biology?

Theoretical biology is a branch of biology that uses mathematical and computational models to understand and predict biological phenomena. It combines principles from biology, physics, and mathematics to study complex systems in living organisms.

What is the role of proofs in theoretical biology?

Proofs are used in theoretical biology to provide mathematical support for hypotheses and theories. They help to validate the accuracy and reliability of models and predictions, and can also reveal limitations and flaws in existing theories.

How does theoretical biology contribute to scientific advancements?

Theoretical biology has played a crucial role in advancing our understanding of complex biological processes, such as evolution, genetics, and ecology. It also allows scientists to make predictions and test hypotheses in a controlled and systematic manner.

What skills are needed to become a theoretical biologist?

To become a theoretical biologist, one must have a strong foundation in mathematics, statistics, and computer science. Additionally, a deep understanding of biological systems and processes is necessary, along with critical thinking and problem-solving skills.

What are some current areas of research in theoretical biology?

Some current areas of research in theoretical biology include network theory, systems biology, and evolutionary game theory. Other topics of interest include population dynamics, disease modeling, and the application of machine learning techniques to biological data.

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