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Cells process signals using complex and dynamic networks. Studying how this is performed in a context and cell type specific way is essential to understand signaling both in physiological and diseased situations. Context-specific medium/high throughput proteomic data measured upon perturbation is now relatively easy to obtain but formalisms that can take(More)
—Statistical Model Checking (SMC) is a computation-ally very efficient verification technique based on selective system sampling. One well identified shortcoming of SMC is that, unlike probabilistic model checking, it cannot be applied to systems featuring nondeterminism, such as Markov Decision Processes (MDP). We address this limitation by developing an(More)
Thiol-linked DNA-gold nanoparticles were used in a novel colorimetric method to detect the presence of specific mRNA from a total RNA extract of yeast cells. The method allowed detection of expression of the FSY1 gene that encodes a specific fructose/H+ symporter in Saccharomyces bayanus PYCC 4565. FSY1 is strongly expressed when the yeast is grown in(More)
Despite the current wealth of high-throughput data, our understanding of signal transduction is still incomplete. Mathematical modeling can be a tool to gain an insight into such processes. Detailed biochemical modeling provides deep understanding, but does not scale well above relatively a few proteins. In contrast, logic modeling can be used where the(More)
Dynamic modelling is one of the cornerstones of systems biology. Many research efforts are currently being invested in the development and exploitation of large-scale kinetic models. The associated problems of parameter estimation (model calibration) and optimal experimental design are particularly challenging. The community has already developed many(More)
Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient methods for many applications. Despite their utility, there is a limited availability of metaheuristic tools. We present MEIGO, an R and Matlab(More)
MOTIVATION Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a(More)
MOTIVATION Many problems of interest in dynamic modeling and control of biological systems can be posed as non-linear optimization problems subject to algebraic and dynamic constraints. In the context of modeling, this is the case of, e.g. parameter estimation, optimal experimental design and dynamic flux balance analysis. In the context of control,(More)
In the last 30 years, many of the mechanisms behind signal transduction, the process by which the cell takes extracellular signals as an input and converts them to a specific cellular phenotype, have been experimentally determined. With these discoveries, however, has come the realization that the architecture of signal transduction, the signaling network,(More)
MOTIVATION The design of de novo circuits with predefined performance specifications is a challenging problem in Synthetic Biology. Computational models and tools have proved to be crucial for a successful wet lab implementation. Natural gene circuits are complex, subject to evolutionary tradeoffs and playing multiple roles. However, most synthetic designs(More)