Bridging long temporal and spatial scales

Research into the origins and evolution of life requires a great deal of imagination from scientists. They have to make comparisons between situations that are billions of years apart. They also must relate molecular processes to entire ecosystems. This requires detailed computer models that can make these leaps in time and scale easy to handle.

Bridging long temporal and spatial scales

All of Origins Center’s Knowledge Networks face these challenges in answering their research questions. Chemical, biological, physical and astrophysical observations, experiments and simulations will yield growing streams of large data which are integrated to generate new knowledge. Therefore, new computational and mathematical methods will be needed. New multi-scale mathematical models help to visualise and better understand the interactions and dependent relationships between biological molecules, cells, organisms and their environment.

In the next five to ten years, the Origins Center has the ambition to push breakthroughs on computational and mathematical methods for multi-scale modeling, simulation and analysis of large, complex data.

1. For the geological and planetary sciences, better scale integration in models and research will lead to new insights into the mechanisms of global change. For example, climate change, changes in geomagnetism and plate tectonics. 

2. For the biological and physical sciences, multi-scale computer models will help us understand how molecules can organise into self-replicating, living cells. But also, how cells can join forces to form multicellular organisms, and how organisms form ecosystems. 

3. For the mathematical sciences, it is becoming increasingly important to predict collective behaviour based on individual behaviour. There is also a great demand for new calculation techniques with which individual behaviour can be analyzed on a large scale in a collective. New mathematical models are more widely applicable than the search for the origin of life and evolution. 

4. Mathematical and data science will have to develop new methods to compare events of different sizes in multi-scale computer models. Examples are the prediction of earthquakes based on seismological vibrations that are measured over a long period of time. Or the prediction of large-scale ecological catastrophes based on several seemingly loose observations in the ecosystem. Large growing datasets are increasingly used for early warnings.

To achieve these goals, the national computing facilities and modern High-Performance Computing (HPC) should be used more intensively.

Origins Center Networks


Roeland Merks

Leiden University

Roeland Merks

Leiden University



Fields of interest:

My team and I work on several topics including modelling of collective cell behavior and the evolution of multicellularity, and the metabolism of microbial community.

Mathematical Biology; multicellular modeling


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