Discovering Dynamic Characteristics of Biochemical Pathways using Geometric Patterns among Parameter-Parameter Dependencies in Differential Equations

Azuma, Ryuzo; Umetsu, Ryo; Ohki, S; Konishi, Fumikazu; Sumi, Y.; Konagaya, Akihiko; Matsumura, Kazumi

doi:10.1007/s00354-007-0027-3

Cited by 3 publications

(3 citation statements)

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“…Graphviz [ 44 ], a graph visualization program designed by Gansner et al, was used to visualize pathways generated by the inference programs. The PPD Viewer designed by Azuma et al [ 12 ] was used for numerical simulation.…”

Section: Methodsmentioning

confidence: 99%

“…We used the parameter-parameter dependency analysis system (PPD Viewer) designed by Konagaya et al [ 12 ], with high-throughput numerical simulation engine and interactive visualization tools developed on OBIGrid [ 3 , 13 - 16 ]. The system can predict the concentration/time profiles and those moment parameters such as area under the curve (AUC), area under the moment curve (AUMC), and mean resident time (MRT) when changing some kinetic parameters in the range of one thousandth to thousands of physiological conditions.…”

Section: Introductionmentioning

confidence: 99%

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Drug interaction prediction using ontology-driven hypothetical assertion framework for pathway generation followed by numerical simulation

et al. 2008

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Background: In accordance with the increasing amount of information concerning individual differences in drug response and molecular interaction, the role of in silico prediction of drug interaction on the pathway level is becoming more and more important. However, in view of the interferences for the identification of new drug interactions, most conventional information models of a biological pathway would have limitations. As a reflection of real world biological events triggered by a stimulus, it is important to facilitate the incorporation of known molecular events for inferring (unknown) possible pathways and hypothetic drug interactions. Here, we propose a new Ontology-Driven Hypothetic Assertion (OHA) framework including pathway generation, drug interaction detection, simulation model generation, numerical simulation, and hypothetic assertion. Potential drug interactions are detected from drug metabolic pathways dynamically generated by molecular events triggered after the administration of certain drugs. Numerical simulation enables to estimate the degree of side effects caused by the predicted drug interactions. New hypothetic assertions of the potential drug interactions and simulation are deduced from the Drug Interaction Ontology (DIO) written in Web Ontology Language (OWL).

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Drug interaction prediction using ontology-driven hypothetical assertion framework for pathway generation followed by numerical simulation

et al. 2008

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“…Mathematical models often have parameter-parameter dependencies that compensate for the effect of certain parameters by means of adjusting other parameters to reproduce the same output (Azuma et al, 2007). This suggests focusing on the analysis of parameter diversities of the solution space, rather than the analysis of an individual virtual patient of the solution space.…”

Section: Distribution Estimationmentioning

confidence: 99%

Towards an In Silico Approach to Personalized Pharmacokinetics

Konagaya¹

2012

Molecular Interactions

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Continuous Description of Discrete Biological Data

Чернышенко

2019

International Journal of Applied Research in Bioinformatics

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The applicability of differential equations to description of integer values dynamics in bio-informatics is investigated. It is shown that a differential model may be interpreted as a continuous analogue of a stochastic flow. The method of construction of a quasi-Poisson flow on the base of multi-dimension differential equations is proposed. Mathematical correctness of the algorithm is proven. The system has been studied by a computer simulation and a discrete nature of processes has been taken into account. The proposed schema has been applied to the classical Volterra's models, which are widely used for description of biological systems. It has been demonstrated that although behaviour of discrete and continuous models is similar, some essential qualitative and quantitative differences in their dynamics take place.

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Discovering Dynamic Characteristics of Biochemical Pathways using Geometric Patterns among Parameter-Parameter Dependencies in Differential Equations

Cited by 3 publications

References 10 publications

Drug interaction prediction using ontology-driven hypothetical assertion framework for pathway generation followed by numerical simulation

Drug interaction prediction using ontology-driven hypothetical assertion framework for pathway generation followed by numerical simulation

Towards an In Silico Approach to Personalized Pharmacokinetics

Continuous Description of Discrete Biological Data

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