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See detailDynamical hybrid modeling of human metabolism
Ben Guebila, Marouen UL

Doctoral thesis (2018)

Human metabolism plays a key role in disease pathogenesis and drug action. Half a century of biochemical literature leveraged by the advent of genomics allowed the emergence of computational modeling ... [more ▼]

Human metabolism plays a key role in disease pathogenesis and drug action. Half a century of biochemical literature leveraged by the advent of genomics allowed the emergence of computational modeling techniques and the in silico analysis of complex biological systems. In particular, Constraint-Based Reconstruction and Analysis (COBRA) methods address the complexity of metabolism through building tissue-specific networks in their steady state. It is known that biological systems respond to perturbations induced by pathogens, drugs or malignant processes by shifting their activity to safeguard key metabolic functions. Extending the modeling framework to consider the dynamics of these complex systems will bring simulations closer to observable human phenotypes. In this thesis, I combined physiologically-based pharmacokinetic (PBPK) models with genome-scale metabolic models (GSMMs) to form hybrid genome-scale dynamical models that provide a hypothesis-free framework to study the perturbations induced by one or more perturbagen on human tissues. On a first stage, these methodologies were applied to decipher the absorption of levodopa and amino acids by the intestinal epithelium and allowed to derive a model-based diet for Parkinson's Disease patients. In the next phase, we extended the study to 605 drugs in order to predict the occurrence of gastrointestinal side effects through a machine learning classifier, using a combination of gene expression and metabolic reactions set as features. Finally, the approach upscaled to several tissues, specifically to investigate the genesis of metabolic symptoms in type 1 diabetes and to suggest key metabolic players underlying within and between-individual variability to insulin action. Taken as whole, the integration of two modeling techniques constrained by expert biological knowledge and heterogeneous data types will be a step forward in achieving convergence in human biology. [less ▲]

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See detailDynamical Modeling Techniques for Biological Time Series Data
Mombaerts, Laurent UL

Doctoral thesis (2019)

The present thesis is articulated over two main topics which have in common the modeling of the dynamical properties of complex biological systems from large-scale time-series data. On one hand, this ... [more ▼]

The present thesis is articulated over two main topics which have in common the modeling of the dynamical properties of complex biological systems from large-scale time-series data. On one hand, this thesis analyzes the inverse problem of reconstructing Gene Regulatory Networks (GRN) from gene expression data. This first topic seeks to reverse-engineer the transcriptional regulatory mechanisms involved in few biological systems of interest, vital to understand the specificities of their different responses. In the light of recent mathematical developments, a novel, flexible and interpretable modeling strategy is proposed to reconstruct the dynamical dependencies between genes from short-time series data. In addition, experimental trade-offs and optimal modeling strategies are investigated for given data availability. Consistent literature on these topics was previously surprisingly lacking. The proposed methodology is applied to the study of circadian rhythms, which consists in complex GRN driving most of daily biological activity across many species. On the other hand, this manuscript covers the characterization of dynamically differentiable brain states in Zebrafish in the context of epilepsy and epileptogenesis. Zebrafish larvae represent a valuable animal model for the study of epilepsy due to both their genetic and dynamical resemblance with humans. The fundamental premise of this research is the early apparition of subtle functional changes preceding the clinical symptoms of seizures. More generally, this idea, based on bifurcation theory, can be described by a progressive loss of resilience of the brain and ultimately, its transition from a healthy state to another characterizing the disease. First, the morphological signatures of seizures generated by distinct pathological mechanisms are investigated. For this purpose, a range of mathematical biomarkers that characterizes relevant dynamical aspects of the neurophysiological signals are considered. Such mathematical markers are later used to address the subtle manifestations of early epileptogenic activity. Finally, the feasibility of a probabilistic prediction model that indicates the susceptibility of seizure emergence over time is investigated. The existence of alternative stable system states and their sudden and dramatic changes have notably been observed in a wide range of complex systems such as in ecosystems, climate or financial markets. [less ▲]

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See detailDynamical properties and characterization of gradient drift diffusions
Darses, Sébastien; Nourdin, Ivan UL

in Electronic Communications in Probability (2007), 12

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See detailDynamical strategies for obstacle avoidance during Dictyostelium discoideum aggregation: a Multi-agent system model
Proverbio, Daniele UL; Maggiora, Marco

E-print/Working paper (2019)

Chemotaxis, the movement of an organism in response to a chemical stimulus, is a typical feature of many microbiological systems. In particular, the social amoeba Disctyostelium discoideum is widely used ... [more ▼]

Chemotaxis, the movement of an organism in response to a chemical stimulus, is a typical feature of many microbiological systems. In particular, the social amoeba Disctyostelium discoideum is widely used as a model organism, but it is not still clear how it behaves in heterogeneous environments. A few models focused on mechanical features have already addressed the question; however, we propose that phenomenological models focusing on the dynamics may provide new meaningful data. Consequently, by means of a specific Multi-agent system model, we studied the dynamical features emerging from complex social interactions among individuals belonging to amoeboids colonies. After defining an appropriate metric to perform meaningful measurements, we found that: a) obstacles play the role of local topological perturbation, as they alter the flux of chemical signals; b) that obstacle that physically block the cellular motion as well as the chemicals elicit dynamical evolutions that are not statistically distinguishable from the case where obstacles that do not interfere physically with said motion; c) that fluctuations of the dynamics can lead to better exploration of the physical space, thus preventing multiple stable aggregates. From previous results, we may speculate about the fact that chemotactic cells, in many cases, can avoid obstacles by simply following the altered chemical gradient: social interactions seem to be sufficient to guarantee the aggregation of the whole colony past numerous obstacles. It is then unlikely that cells have developed special mechanisms to cope with the presence of topological perturbation sources. Nevertheless, we suggest that further studies can provide better understanding and that, in order to gain deeper knowledge, mechanical models should be coupled with phenomenological, system-oriented ones. [less ▲]

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See detailDynamical structure analysis of sparsity and minimality heuristics for reconstruction of biochemical networks
Howes, R.; Eccleston, L. J.; Goncalves, Jorge UL et al

in The proceedings of the 47th IEEE Conference on Decision and Control (2008)

Network reconstruction, i.e. obtaining network structure from input-output information, is a central theme in systems biology. A variety of approaches aim to obtaining structural information from ... [more ▼]

Network reconstruction, i.e. obtaining network structure from input-output information, is a central theme in systems biology. A variety of approaches aim to obtaining structural information from available data. Previous work has introduced dynamical structure functions as a tool for posing and solving the network reconstruction problem. Even for linear time invariant systems, reconstruction requires specific additional information not generated in the typical system identification process. This paper demonstrates that such extra information can be obtained through a limited sequence of system identification experiments on structurally modified systems, analogous to gene silencing and overexpression experiments. In the absence of such extra information, we discuss whether combined assumptions of network sparsity and minimality contribute to the recovery of the network dynamical structure. We provide sufficient conditions for a transfer function to have a completely decoupled minimal realization, and demonstrate that every transfer function is arbitrarily close to one that admits a perfectly decoupled minimal realization. This indicates that the assumptions of sparsity and minimality alone do not lend insight into the network structure. [less ▲]

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See detailDynamical Structure Function and Granger Causality: Similarities and Differences
Yue, Zuogong UL; Thunberg, Johan UL; Yuan, Ye et al

in 54th IEEE Conference on Decision and Control, Osaka, Japan, December 15-18, 2015 (2015)

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See detailDynamical structure function identifiability conditions enabling signal structure reconstruction
Adebayo, J.; Southwick, T.; Chetty, V. et al

in The proceedings of the 51st IEEE Conference on Decision and Control (CDC) (2012, December)

Networks of controlled dynamical systems exhibit a variety of interconnection patterns that could be interpreted as the structure of the system. One such interpretation of system structure is a system's ... [more ▼]

Networks of controlled dynamical systems exhibit a variety of interconnection patterns that could be interpreted as the structure of the system. One such interpretation of system structure is a system's signal structure, characterized as the open-loop causal dependencies among manifest variables and represented by its dynamical structure function. Although this notion of structure is among the weakest available, previous work has shown that if no a priori structural information is known about the system, not even the Boolean structure of the dynamical structure function is identifiable. Consequently, one method previously suggested for obtaining the necessary a priori structural information is to leverage knowledge about target specificity of the controlled inputs. This work extends these results to demonstrate precisely the a priori structural information that is both necessary and sufficient to reconstruct the network from input-output data. This extension is important because it significantly broadens the applicability of the identifiability conditions, enabling the design of network reconstruction experiments that were previously impossible due to practical constraints on the types of actuation mechanisms available to the engineer or scientist. The work is motivated by the proteomics problem of reconstructing the Per-Arnt-Sim Kinase pathway used in the metabolism of sugars. [less ▲]

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See detailDynamical structure functions for the reverse engineering of LTI networks
Goncalves, Jorge UL; Howes, R.; Warnick, S.

in Proceedings of the 46th IEEE Conference on Decision and Control (2007)

This research explores the role and representation of network structure for LTI systems with partial state observations. We demonstrate that input-output representations, i.e. transfer functions, contain ... [more ▼]

This research explores the role and representation of network structure for LTI systems with partial state observations. We demonstrate that input-output representations, i.e. transfer functions, contain no internal structural information of the system. We further show that neither the additional knowledge of system order nor minimality of the true realization is generally sufficient to characterize network structure. We then introduce dynamical structure functions as an alternative, graphical-model based representation of LTI systems that contain both dynamical and structural information of the system. The main result uses dynamical structure to precisely characterize the additional information required to obtain network structure from the transfer function of the system. [less ▲]

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See detailDynamics and feedback loops in the transforming growth factor beta signaling pathway.
Wegner, Katja; Bachmann, Anastasia; Schad, Jan-Ulrich et al

in Biophysical chemistry (2012), 162

Transforming growth factor beta (TGF-beta) ligands activate a signaling cascade with multiple cell context dependent outcomes. Disruption or disturbance leads to variant clinical disorders. To develop ... [more ▼]

Transforming growth factor beta (TGF-beta) ligands activate a signaling cascade with multiple cell context dependent outcomes. Disruption or disturbance leads to variant clinical disorders. To develop strategies for disease intervention, delineation of the pathway in further detail is required. Current theoretical models of this pathway describe production and degradation of signal mediating proteins and signal transduction from the cell surface into the nucleus, whereas feedback loops have not exhaustively been included. In this study we present a mathematical model to determine the relevance of feedback regulators (Arkadia, Smad7, Smurf1, Smurf2, SnoN and Ski) on TGF-beta target gene expression and the potential to initiate stable oscillations within a realistic parameter space. We employed massive sampling of the parameters space to pinpoint crucial players for potential oscillations as well as transcriptional product levels. We identified Smad7 and Smurf2 with the highest impact on the dynamics. Based on these findings, we conducted preliminary time course experiments. [less ▲]

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See detailThe Dynamics Implications of Liberalizing Global Migration
Delogu, Marco UL

E-print/Working paper (2013)

Detailed reference viewed: 90 (11 UL)
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See detailDynamics in Argumentation with Single Extensions: Abstraction Principles and the Grounded Extension
Boella, Guido UL; Kaci, Souhila UL; van der Torre, Leon UL

in Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 10th European Conference, ECSQARU 2009, Verona, Italy, July 1-3, 2009. Proceedings (2009)

In this paper we consider the dynamics of abstract argumentation in Baroni and Giacomin’s framework for the evaluation of extension based argumentation semantics. Following Baroni and Giacomin, we do not ... [more ▼]

In this paper we consider the dynamics of abstract argumentation in Baroni and Giacomin’s framework for the evaluation of extension based argumentation semantics. Following Baroni and Giacomin, we do not consider individual approaches, but we define general principles or postulates that individual approaches may satisfy. In particular, we define abstraction principles for the attack relation, and for the arguments in the framework. We illustrate the principles on the grounded extension. In this paper we consider only principles for the single extension case, and leave the multiple extension case to further research. [less ▲]

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See detailDynamics in Delegation and Revocation Schemes: A Logical Approach
Aucher, Guillaume UL; Barker, Steve; Boella, Guido UL et al

in DBSec (2011)

In this paper we first introduce a logic for describing formally a family of delegation and revocation models that are based on the work in Hagström et al.. We then extend our logic to accommodate an ... [more ▼]

In this paper we first introduce a logic for describing formally a family of delegation and revocation models that are based on the work in Hagström et al.. We then extend our logic to accommodate an epistemic interpretation of trust within the framework that we define. What emerges from this work is a rich framework of formally well-defined delegation and revocation schemes that accommodates an important trust component. [less ▲]

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See detailDynamics maps for long-term autonomy
Ginés, J.; Martín, F.; Matellán, V. et al

in 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) (2017)

Navigating is one of the most basic capabilities of mobile robots. For this task, robots usually represent the environment through maps. This paper reports on first results of a work focused on mapping ... [more ▼]

Navigating is one of the most basic capabilities of mobile robots. For this task, robots usually represent the environment through maps. This paper reports on first results of a work focused on mapping dynamic environments to achieve a robust navigation for long-term operation. This approach builds a static map starting from the construction plans of a building. A long-term map is started from the static map, and updated when adding and removing furniture, or when doors are opened or closed. A short-term map represents dynamic obstacles such as people. This approach is appropriate for fast deployment and long-term operations in office or domestic environments, able to adapt to changes in the environment. We demonstrate the robustness of this approach in the RoboCup@home competition, where robots must navigate in an environment that changes during the tests. [less ▲]

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See detailThe Dynamics of Agglomeration: Evidence from Ireland and Portugal
Barrios, Salvador; Bertinelli, Luisito UL; Strobl, Eric et al

in Journal of Urban Economics (2005), 57(1), 170-188

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See detailDynamics of Blockchain Implementation : A Case Study from the Energy Sector
Albrecht, Simon; Reichert, Stefan; Schmid, Jan et al

in 51st Hawaii International Conference on System Sciences (2018)

This case study analyzes the impact of theory-based factors on the implementation of different blockchain technologies in use cases from the energy sector. We construct an integrated research model based ... [more ▼]

This case study analyzes the impact of theory-based factors on the implementation of different blockchain technologies in use cases from the energy sector. We construct an integrated research model based on the Diffusion of Innovations theory, institutional economics and the Technology-Organization-Environment framework. Using qualitative data from in-depth interviews, we link constructs to theory and assess their impact on each use case. Doing so we can depict the dynamic relations between different blockchain technologies and the energy sector. The study provides insights for decision makers in electric utilities, and government administrations. [less ▲]

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See detailDynamics of electron-emission currents in plasmonic gaps induced by strong fields
Aguirregabiria, Garikoitz; Marinica, Dana-Codruta; Ludwig, Markus et al

in FARADAY DISCUSSIONS (2019), 214

The dynamics of ultrafast electron currents triggered by femtosecond laser pulse irradiation of narrow gaps in a plasmonic dimer is studied using quantum mechanical Time-Dependent Density Functional ... [more ▼]

The dynamics of ultrafast electron currents triggered by femtosecond laser pulse irradiation of narrow gaps in a plasmonic dimer is studied using quantum mechanical Time-Dependent Density Functional Theory (TDDFT). The electrons are injected into the gap due to the optical field emission from the surfaces of the metal nanoparticles across the junction. Further evolution of the electron currents in the gap is governed by the locally enhanced electric fields. The combination of TDDFT and classical modelling of the electron trajectories allows us to study the quiver motion of the electrons in the gap region as a function of the Carrier Envelope Phase (CEP) of the incident pulse. In particular, we demonstrate the role of the quiver motion in establishing the CEP-sensitive net electric transport between nanoparticles. [less ▲]

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See detailThe Dynamics of Firms Location: A Revisit of Home Attachment under Tax Competition
Han, Yutao UL; Pieretti, Patrice UL; Zou, Benteng UL

in Economics Letters (2013), 121

In this short note we extend the home attachment setting of Mansoorian and Myers (1993) and Ogura (2006) to allow the study of tax competition in a dynamic framework when international business relocation ... [more ▼]

In this short note we extend the home attachment setting of Mansoorian and Myers (1993) and Ogura (2006) to allow the study of tax competition in a dynamic framework when international business relocation occurs over successive periods. The dynamic framework we propose also helps to understand why tax rates may change over time. Our modified home-attachment rule is illustrated by a simple model of dynamic tax competition in discrete time. [less ▲]

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See detailThe Dynamics of Freight Transport Development: A UK and Swiss Comparison
Hesse, Markus UL

in Journal of Transport Geography (2006), 14(1), 78-79

Detailed reference viewed: 37 (0 UL)
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See detailThe Dynamics of Heat Shock Response Induced by Ultr asound Therapeutic Treatment
Mizera, Andrzej UL; Gambin, Barbara

in Awrejcewicz, J.; Kaźmierczak, M.; Mrozowski, J. (Eds.) et al 10th Conference on Dynamical Systems – Theory and Applications, DSTA-2009 (2009)

Detailed reference viewed: 27 (1 UL)