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Elucidating the molecular mechanisms that govern plant growth has been an important topic in plant research, and current advances in large-scale data generation call for computational tools that efficiently combine these different data sources to generate novel hypotheses. In this work, we present a novel, integrated network that combines multiple large-scale data sources to characterize growth regulatory genes in Arabidopsis, one of the main plant model organisms.

Initial community evenness has been shown to be a key factor in preserving the functional stability of an ecosystem, but has not been accounted for in previous modelling studies. We formulate a model that allows the initial evenness of the community to be varied in order to investigate the consequent impact on system diversity. We consider a community of four interacting bacterial species, and present a stochastic, spatial individual-based model simulating the ecosystem dynamics. Interactions take place on a two-dimensional lattice.

MULTIMOT is a H2020 EU funded project that aims to build an open data ecosystem for cell migration research, through standardization, dissemination and meta-analysis efforts.The Componics lab of BIG N2N partner Lennart Martens is participating. Prof. Martens and collaborators explain their contribution to the project in this movie: https://www.youtube.com/watch?v=Iwz0uQNJr0Q.

In recent years, rising energy prices and increasing environmental concerns have boosted research in the so called green ICT and green networking research tracks, aimed at improving the energy efficiency of communications while still offering maximal functionality. In this article we explore a future scenario in which low power networking is no longer optional, but instead becomes a necessity due to fluctuating energy availability. The contribution of this work is twofold.