Es sei bei weitem leichter für einen Wissenschaftler, eine benötigte Zusammenarbeit mit einem Mathematiker oder Statistiker anzugehen, statt umgekehrt für einen Mathematiker, einen Wissenschaftler zu finden, der seine Gleichungen benutzen kann. So äußerte sich 2013 der Biologe Edward O. Wilson im The Wall Street Journal.
Diese Aussage reflektiert nach Hans Othmer, Professor für Mathematik an der University of Minnesota, das völlige Unverständnis der Rolle der Mathematik in der Wissenschaft. 1996 habe ich bei Hans Othmer Vorlesungen über mathematische Biologie gehört. Heute Abend kann ich erneut über das Internet einen Vortrag von ihm zuhören. Eine kurze Zusammenfassung (abstract) dieses Vortrages ist unten angeführt.
Wer den Vortrag auch folgen will, kann hier einen Link zum Live Stream anfordern.
In a Wall Street Journal article published in 2013, E. O. Wilson attempted to make the case that biologists don’t really need to learn any mathematics — whenever they run into difficulty with numerical issues they can find a technician (aka mathematician) to help them out of their difficulty. He formalizes this in Wilson’s Principle No. 1: „It is far easier for scientists to acquire needed collaboration from mathematicians and statisticians than it is for mathematicians and statisticians to find scientists able to make use of their equations.“ This reflects a complete misunderstanding of the role of mathematics in all sciences throughout history. To Wilson mathematics is mere number crunching, but as Galileo said long ago, The laws of Nature are written in the language of mathematics… the symbols are triangles, circles and other geometrical figures, without whose help it is impossible to comprehend a single word. Mathematics has moved beyond the geometry-based model of Galileo’s time, and in a rebuttal to Wilson, E. Frenkel has pointed out the role of mathematics in synthesizing the general principles in science. In this talk we will take this a step further and show how mathematics has been used to make new and experimentally-verified discoveries and how mathematics is essential for understanding a problem that has puzzled experimentalists for decades — that of how organisms can scale in size. Mathematical analysis alone cannot „solve“ these problems since the validation lies at the molecular level, but conversely, a growing number of questions in biology cannot be solved without mathematical analysis and modeling. We will highlight a few instances where modeling has been used to push experiments forward and highlight problems in biology that cannot be adequately addressed without mathematical modeling.