Mathematical modeling has recently become a much-lauded enterprise, and many funding agencies seek to prioritize this endeavor. However, there are certain dangers associated with mathematical modeling, and knowledge of these pitfalls should also be part of a biologist\u27s training in this set of techniques. (1) Mathematical models are limited by known science; (2) Mathematical models can tell what can happen, but not what did happen; (3) A model does not have to conform to reality, even if it is logically consistent; (4) Models abstract from reality, and sometimes what they eliminate is critically important; (5) Mathematics can present a Platonic ideal to which biologically organized matter strives, rather than a trial-and-error bumbling t...
The vast diversity of topics that appear in this special issue BIOMATH 2011 is indicative of how mat...
Biology has become the new “physics” of mathematics, one of the areas of greatest mathematical appli...
Biological systems are staggeringly complex. To untangle this complexity and make predictions about ...
Mathematical modeling has recently become a much-lauded enterprise, and many funding agencies seek t...
Mathematical modelling has been proven to be useful in understanding some problems from biological s...
Models have made numerous contributions to evolutionary biology, but misunderstandings persist regar...
Understanding modeling in biology requires understanding how biology is organized as a discipline an...
In this essay I will sketch some ideas for how to think about models in biology. I will begin by try...
Progress in science often begins with verbal hypotheses meant to explain why certain biological phen...
This special issue of Mathematical Modelling of Natural Phenomena on biomathematics education shares...
Mathematical manipulative models have had a long history of influence in biological research and in ...
We provide a critique of mathematical biology in light of rapid developments in modern machine learn...
Mathematical biology has been an area of wide interest during the recent decades, as the modeling of...
Theoretical ideas have a rich history in many areas of biology, and new theories and mathematical mo...
Biology is a source of fascination for most scientists, whether their training is in the life scienc...
The vast diversity of topics that appear in this special issue BIOMATH 2011 is indicative of how mat...
Biology has become the new “physics” of mathematics, one of the areas of greatest mathematical appli...
Biological systems are staggeringly complex. To untangle this complexity and make predictions about ...
Mathematical modeling has recently become a much-lauded enterprise, and many funding agencies seek t...
Mathematical modelling has been proven to be useful in understanding some problems from biological s...
Models have made numerous contributions to evolutionary biology, but misunderstandings persist regar...
Understanding modeling in biology requires understanding how biology is organized as a discipline an...
In this essay I will sketch some ideas for how to think about models in biology. I will begin by try...
Progress in science often begins with verbal hypotheses meant to explain why certain biological phen...
This special issue of Mathematical Modelling of Natural Phenomena on biomathematics education shares...
Mathematical manipulative models have had a long history of influence in biological research and in ...
We provide a critique of mathematical biology in light of rapid developments in modern machine learn...
Mathematical biology has been an area of wide interest during the recent decades, as the modeling of...
Theoretical ideas have a rich history in many areas of biology, and new theories and mathematical mo...
Biology is a source of fascination for most scientists, whether their training is in the life scienc...
The vast diversity of topics that appear in this special issue BIOMATH 2011 is indicative of how mat...
Biology has become the new “physics” of mathematics, one of the areas of greatest mathematical appli...
Biological systems are staggeringly complex. To untangle this complexity and make predictions about ...