Modelling as a service

Mathematical models are essential in systems biology, connecting knowledge into a predictive, testable whole. How can modelling be provided as a service by an infrastructure?

One of the proposed centre types for ISBE is the Data Integration Centre, or Modelling Centre. In this way ISBE aims to provide modelling as a service, and to connect experimentalists with theoreticians according to their needs. This approach distinguishes ISBE from most infrastructural networks for generating and sharing biological data; we anticipate it will require a decentralised structure to better activate and access the intellectual capital that exists for modelling in Europe.

Top modellers are distributed over many institutions; a hub structure would facilitate their contributions to ISBE services while allowing modellers the freedom to pursue many different career paths. Key tasks for the ISBE hub would be to certify modelling expertise, and to mediate contact between clients and the modellers working within ISBE.

What is a model?

A model is a purposeful simplification of reality, designed to imitate certain phenomena or characteristics of a system while downplaying non-essential aspects. Formulating knowledge in mathematical models enables analysis by the rules of algebra, or by computer simulation, whose insights may generalize to the whole class of systems that it represents. Simulation experiments can be designed to closely mirror real experiments (for confrontation with relevant data), or to explore scenarios that are too expensive, time-consuming or risky to perform in real life. It can take a huge scientific investment to develop a model from scratch, and often even to apply existing models to new data or circumstances.

The capabilities of mathematical modelling

  • Connecting a comprehensive amount of empirical data into a functional whole
  • Enforcing more explicit formulations of various hypotheses
  • Increasing the prediction space of hypotheses
  • Initiating and canalizing experimental or empirical work by pointing out key questions and the type of data needed
  • Ensuring that models and ’ways of thinking’ are consistent with fundamental principles of physics, chemistry, and biology
  • Functioning as highly efficient intellectual meeting places for various disciplines.