Team:Marburg/Model

M O D E L L I N G


The "Unreasonable Effectiveness of Mathematics in the Natural Sciences" is the title of a very well-known article published by nobel laureate Eugene Wigner in the 1960s. Although this dictum is common reality in fields such as physics, many biologists still neglect the usefulness of these rigorous methods.

This year, our interdisciplinary team has worked hard to change this impression and incorporated many state-of-the-art methods from various scientific fields into the project. We put a high emphasis on standardization which has emerged from a yearning for a meticulous quantitative approach to cyanobacterial research. In particular, our interest laid in determining the optimal growth parameters of our organism S. elongatus as these differed greatly in literature. The development of a state-of-the-art machine learning model allowed us to rapidly speed up this process and guide us towards our ultimate goal. In order to extend our standardization efforts, we additionally implemented a light model to properly predict light intensities for our cultures.

Furthermore, modelling played a crucial role in both the search/design of suitable genome integration sites as well as the construction of a synthetic terminator library based on an extensive biophysical model. Without these rigorous analytical methods our project would have been unfeasible.


G R O W T H   C U R V E
M O D E L


A R T I F I C I A L   N E U T R A L
I N T E G R A T I O N
S I T E   O P T I O N S


T E R M I N A T O R
M O D E L