A divide-and-conquer approach to analyze underdetermined biochemical models

Motivation: To obtain meaningful predictions from dynamic computational models, their uncertain parameter values need to be estimated from experimental data. Due to the usually large number of parameters compared to the available measurement data, these estimation problems are often underdetermined meaning that the solution is a multidimensional space. In this case, the challenge is yet to obtain a sound system understanding despite non-identifiable parameter values, e.g. through identifying those parameters that most sensitively determine the model's behavior. Results: Here, we present the so-called divide-and-conquer approach—a strategy to analyze underdetermined biochemical models. The approach draws on steady state omics measurement data and exploits a decomposition of the global estimation problem into independent subproblems. The solutions to these subproblems are joined to the complete space of global optima, which can be easily analyzed. We derive the conditions at which the decomposition occurs, outline strategies to fulfill these conditions and—using an example model—illustrate how the approach uncovers the most important parameters and suggests targeted experiments without knowing the exact parameter values. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Context Awareness for Self-adaptive and Highly Available Production Systems

Part 8: Robotics and ManufacturingInternational audienceA new approach for the realization of self-adaptive and highly available production systems based on a context aware approach, allowing self-adaptation of flexible manufacturing processes in production systems and effective knowledge sharing to support maintenance, is presented. The usage of dynamically changing context as basis for adaptation of flexible manufacturing lines/processes and effective knowledge sharing is proposed. The presented solution includes services for context extraction, adaptation and self-learning allowing high adaptation of production systems depending on the identified context. A generic architecture following Service Oriented Principles is presented allowing for integration of the proposed solution into various production systems. A successful initial application of the developed solution in real world manufacturing environment is presented

A divide-and-conquer approach to analyze underdetermined biochemical models

Motivation: To obtain meaningful predictions from dynamic computational models, their uncertain parameter values need to be estimated from experimental data. Due to the usually large number of parameters compared to the available measurement data, these estimation problems are often underdetermined meaning that the solution is a multidimensional space. In this case, the challenge is yet to obtain a sound system understanding despite non-identifiable parameter values, e.g. through identifying those parameters that most sensitively determine the model’s behavior. Results: Here, we present the so-called divide-and-conquer approach—a strategy to analyze underdetermined biochemical models. The approach draws on steady state omics measurement data and exploits a decomposition of the global estimation problem into independent subproblems. The solutions to these subproblems are joined to the complete space of global optima, which can be easily analyzed. We derive the conditions at which the decomposition occurs, outline strategies to fulfill these conditions and—using an example model—illustrate how the approach uncovers the most important parameters and suggests targeted experiments without knowing the exact parameter values.

Bacterial adaptation through distributed sensing of metabolic fluxes

We present a large-scale differential equation model of E. coli's central metabolism and its enzymatic, transcriptional, and posttranslational regulation. This model reproduces E. coli's known physiological behavior.We found that the interplay of known interactions in E. coli's central metabolism can indirectly recognize the presence of extracellular carbon sources through measuring intracellular metabolic flux patterns.We found that E. coli's system-level adaptations between glycolytic and gluconeogenic carbon sources are realized on the molecular level by global feedback architectures that overarch the enzymatic and transcriptional regulatory layers.We found that the capability for closed-loop self-regulation can emerge within metabolism itself and therefore, metabolic operation may adapt itself autonomously to changing carbon sources (not requiring upstream sensing and signaling)

Living with an imperfect cell wall: compensation of femAB inactivation in Staphylococcus aureus

Background: Synthesis of the Staphylococcus aureus peptidoglycan pentaglycine interpeptide bridge is catalyzed by the nonribosomal peptidyl transferases FemX, FemA and FemB. Inactivation of the femAB operon reduces the interpeptide to a monoglycine, leading to a poorly crosslinked peptidoglycan. femAB mutants show a reduced growth rate and are hypersusceptible to virtually all antibiotics, including methicillin, making FemAB a potential target to restore β-lactam susceptibility in methicillin-resistant S. aureus (MRSA). Cis-complementation with wild type femAB only restores synthesis of the pentaglycine interpeptide and methicillin resistance, but the growth rate remains low. This study characterizes the adaptations that ensured survival of the cells after femAB inactivation. Results: In addition to slow growth, the cis-complemented femAB mutant showed temperature sensitivity and a higher methicillin resistance than the wild type. Transcriptional profiling paired with reporter metabolite analysis revealed multiple changes in the global transcriptome. A number of transporters for sugars, glycerol, and glycine betaine, some of which could serve as osmoprotectants, were upregulated. Striking differences were found in the transcription of several genes involved in nitrogen metabolism and the arginine-deiminase pathway, an alternative for ATP production. In addition, microarray data indicated enhanced expression of virulence factors that correlated with premature expression of the global regulators sae, sarA, and agr. Conclusion: Survival under conditions preventing normal cell wall formation triggered complex adaptations that incurred a fitness cost, showing the remarkable flexibility of S. aureus to circumvent cell wall damage. Potential FemAB inhibitors would have to be used in combination with other antibiotics to prevent selection of resistant survivors

An exploratory case study of Olympiad students’ attitudes towards and passion for science

Much is known about high school students’ attitudes towards science but there is almost no research on what passion for science might look like and how it might be manifested. This exploratory case study took advantage of a unique group of highly gifted science students participating in the Australian Science Olympiad (n=69) to explore their attitudes towards school science and science as presented in the Olympiad summer camp. In particular the role the summer camp might play in igniting the students’ passion for science was a focus of the research. Data were collected through a two tiered survey of students’ attitudes towards school science, an evaluative survey of the Olympiad summer camp and in-depth interviews with six participants. Findings indicated that Olympiad students generally had positive attitudes towards school science with most selecting science as one of their favourite subjects. However, an underlying ambivalence about school science was noted in the data. In contrast, the Olympiad summer camp transformed students’ positive attitudes into passion for science. Seven themes emerged from the data providing a foundation for a model of what academic passion for science looks like

Application of Image Processing Techniques for Lamb Wave Characterization

Characterization of dispersion curves in plate-like structures is possible with guided Lamb waves. In this research, experimental development of dispersion curves relies on the spectrogram, which suffers from the Heisenberg Uncertainty Principle. Reassignment is capable of localizing ill--defined dispersion curves. Unfortunately, reassignment also introduces spurious components, which reduce reassignment performance. This research develops an algorithm that provides both localization of dispersion curves and elimination of spurious components. To achieve this, an alternative formulation of reassignment called differential reassignment is modified and superimposed with nonlinear anisotropic diffusion. This study first examines reassignment and diffusion components individually. Three different versions of differential reassignment are considered, two of which are modifications explicitly derived in this research. The combined algorithm is then applied to reassign experimentally measured spectrograms, leading to a significant increase in clarity and notch detection performance.M.S.Committee Chair: Jacobs, Laurence; Committee Member: DesRoches, Reginald; Committee Member: Qu, Jianmi