Integrative Systems Biology Unit
Despite the intrinsic uncertainty in the occurrence of chemical events, and being embedded within fluctuating environments, cells prevail as efficient decision makers. The underlying mechanisms of this ability remain widely unknown, but they are critical for the correct understanding of biological systems output and predictability.
Some advances in deepening the understanding of signalling pathways have been achieved by considering biological processes as modular units, but the conclusions in many studies vary alongside experimental conditions, or easily break down once the system is no longer isolated. Moreover, on top of experimental difficulties, much work is still to be done in order to make accurate simulations of biological processes in relevant ‘real time’ spans a reality, and the selection of a modelling regime clearer. In fact, an integrative view of biology requires a ‘multiscale’ description. This may sound trivial, but the reality is far from that: no existing algorithm can account for all scales operating between the ‘nano’ and the ‘macro’.
In response to these needs, the Integrative Systems Biology unit ‘backbone’ research includes: (1) construction of novel multiscale simulation methods encompassing stochastic and deterministic regimes, (2) stochastic parameter estimation techniques, (3) methodologies for the correct assessment of different sources of noise, and (4) experimental design and implementation of basic biological ‘circuits’. All these tools are subsequently applied to specific cell signalling models and a more complete description of epigenetics and eukaryotic gene expression.
Interested postdoctoral candidates and PhD research interns should contact Prof. Márquez-Lago by email (tatiana.marquez at oist.jp) , including a CV and brief statement of research interests.