Dr Andrea Rocco

Molecular networks, such as gene regulatory networks or metabolic networks, are affected by stochastic fluctuations. Fluctuations due to low copy numbers of proteins, or to gene expression bursts, define so-called 'intrinsic' noise, while fluctuations originating in the environment are usually referred to as 'extrinsic' noise. This part of my research concerns the study of both intrinsic and extrinsic noise, and of their interplay. In particular, extrinsic noise can have highly non-trivial and counterintuitive effects, which may lead to noise-induced transitions [Rocco , in “Systems Biology of Tuberculosis”, Springer (2013)]. Consideration of these effects has led me to introduce the concept of stochastic control in metabolic networks [Rocco, Phys. Biol. (2009)], where noise itself is proven to be able to act as a control mechanism that tunes metabolic concentrations and fluxes. I am now interested in the principles underpinning noise propagation across different layers of regulation in gene networks.

A major problem in developmental biology is to explain the emergence of different cell types from multipotent stem cells. In collaboration with (University of Bath), we have constructed the first core gene regulatory network describing stable differentiation of melanocytes in zebrafish [Greenhill , PLoS Genetics (2011)]. By using a combination of mathematical analysis and simulations, we could predict mathematically and validate experimentally several new features of this network. More recently we have refined that core network, to include an analysis of the role played by Wnt signaling in melanocyte differentiation [Vibert , Pigment Cell & Melanoma Research (2017)]. We are now interested in assessing the role played by noise, both intrinsic and extrinsic, in the dynamics of the differentiation process. More details in our dedicated website. We acknowledge the UK Biotechnology and Biological Sciences Research Council (BBSRC) for funding.

Stochastic fluctuations are at the base of much of the variability that we see in biology. Different phenotypes are well known to arise in populations of genetically identical cells in the same environment. It is an intriguing conjecture that this variability is under positive selection. Yet, what precisely its origin is remains an unanswered question. The requirement that distinct phenotypes be observable over typical experimental times suggests that they result from static heterogeneities in the population, which distinguish individual cells from each other. In collaboration with (University of Surrey), we have recently investigated the possibility that such static heterogeneities are in fact produced by the stochastic bursting activity of gene expression, supplemented with specific mechanisms capable of slowing down fluctuations. To explain this mechanism in general terms, we have introduced in the context of bacterial growth the concept of 'ergodicity breaking', borrowed from statistical mechanics and dynamical systems theory. This has also led us to a novel explanation of the phenomenon of so-called bacterial persistence, or drug tolerance [Rocco , PLoS ONE (2013)]. The proposed mechanism is currently under experimental validation.

In my group we are also investigating the effect that stochastic fluctuations may have on the reduced dynamics of a quantum system. Fluctuations in the environment of the system, as well as intrinsic fluctuations, may break the time-scale separation between system of interest and thermal bath, which is at the basis of the derivation of Markovian (memory-less) reduced quantum-mechanical descriptions. When memory is present, the resulting quantum master equations for the reduced density operator are not expected to satisfy the celebrated Lindblad form, and can show non-trivial dynamics. In particular we are interested in analyzing the effect of correlated noise on the continuum measurement process exerted by the environment on the system of interest, and in turn on its decoherence times. We also aim to investigate the possible relevance of these processes in a biological context.

In the past, I have been involved in the study of branching of gas discharges (so-called streamers), and in the development of the related description in terms of conformal mapping techniques [see for instance Ebert , Plasma Sources Sci. Technol. (2006) for a review]. I also studied the effect of extrinsic noise on the propagation of reaction-diffusion fronts. In the case of the so-called Fisher Equation (FKPP), I contributed to identifying the anomalous sub-diffusive behaviour characterizing the front position [Rocco , Phys. Rev. E (2000)], and to generalize it through the definition of a new roughness universality class for travelling waves in 2 bulk dimensions [Tripathy Phys. Rev. Lett. (2001)]. In the context of off-equilibrium statistical mechanics, I also addressed fundamental issues on complexity reduction in models for glasses [Crisanti , J. Chem. Phys. (2000)]. During my PhD, I developed fractional calculus techniques to study fractal phenomena in both space and time [Rocco & West, Physica (1999); Grigolini , Phys. Rev. E (1999)].