scholarly journals DMPy: a Python package for automated mathematical model construction of large-scale metabolic systems

2018 ◽  
Vol 12 (1) ◽  
Author(s):  
Robert W. Smith ◽  
Rik P. van Rosmalen ◽  
Vitor A. P. Martins dos Santos ◽  
Christian Fleck
Keyword(s):  
Mathematical Model ◽  
Large Scale ◽  
Model Construction ◽  
Metabolic Systems ◽  
Python Package

scholarly journals moped - A Python package for metabolic modelling and topological analysis

2020 ◽  
Author(s):  
Nima P. Saadat ◽  
Marvin van Aalst ◽  
Oliver Ebenhöh
Keyword(s):  
Differential Equations ◽  
Metabolic Networks ◽  
De Novo ◽  
Wide Spectrum ◽  
Topological Analysis ◽  
Model Construction ◽  
Dynamic Simulations ◽  
Analysis Methods ◽  
Metabolic Systems ◽  
Python Package

AbstractBackgroundMathematical modeling of metabolic networks is a powerful approach to investigate the underlying principles of metabolism and growth. Such approaches include, amongst others, differential equations based modeling of metabolic systems, constraint based modeling and topological analysis of metabolic networks. Most of these methods are well established and are implemented in numerous software packages, but these are scattered between different programming languages, packages and syntaxes. This complicates establishing straight forward pipelines integrating model construction and simulation.ResultsWe present the Python package moped which serves as an integrative hub for constructing, modifying and analysing metabolic models. moped supports the de novo construction of models directly from genome sequences and pathway/genome databases, providing a completely reproducible model construction and curation process. Alternatively, existing models published in SBML format can be easily imported. Models are represented as Python objects, for which a wide spectrum of easy-to-use modification and analysis methods exist. The model structure can be manually altered by adding, removing or modifying reactions, and gaps can be filled automatically. This greatly supports the development of curated models. Moreover, moped provides several analysis methods, in particular including the calculation of biosynthetic capacities using metabolic network expansion. The integration with other Python based tools is facilitated through various model export options. For example, a model can be directly converted into a cobrapy object for constraint-based analyses. Likewise, conversion into a modelbase object supports dynamic simulations using ordinary differential equations.Conclusionmoped is a fully documented and expandable Python package. We demonstrate the capability to serve as a hub for integrating model construction, database import, topological analysis and export for constraint-based and kinetic analyses.

scholarly journals Viola: a structural variant signature extractor with user-defined classifications

2021 ◽  
Author(s):  
Itsuki Sugita ◽  
Shohei Matsuyama ◽  
Hiroki Dobashi ◽  
Daisuke Komura ◽  
Shumpei Ishikawa
Keyword(s):  
Large Scale ◽  
Computational Time ◽  
Structural Variant ◽  
Analytical Functions ◽  
Dna Variations ◽  
Python Package

Here, we present Viola, a Python package that provides structural variant (SV; large scale genome DNA variations that can result in disease, e.g., cancer) signature analytical functions and utilities for custom SV classification, merging multi-SV-caller output files, and SV annotation. We demonstrate that Viola can extract biologically meaningful SV signatures from publicly available SV data for cancer and we evaluate the computational time necessary for annotation of the data.

Traffic Fuzzy Controller's Improvement Based on Self-Adaptive Optimal Algorithm

2012 ◽  
Vol 562-564 ◽  
pp. 1414-1417
Author(s):  
Zhi Yi Xu ◽  
Da Lu Guan ◽  
Ai Long Fan
Keyword(s):  
Mathematical Model ◽  
Large Scale ◽  
Fuzzy Controller ◽  
Optimal Algorithm ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Time Varying ◽  
Large Scale Systems ◽  
Simulation Results ◽  
Self Adaptive

The transport system is a nonlinear, time-varying, lagging large-scale systems. Fuzzy control does not need to build a precise mathematical model, can be easily integrated people's thinking and experience, and is suitable for applications in the traffic signal control system. Here,a self-adaptive optimal algorithm was used to improve the traditional fuzzy controller. Simulation results show that the improved system has higher availability.

Tsunamis

2017 ◽  
Author(s):  
John A. Adam
Keyword(s):  
Mathematical Model ◽  
Large Scale ◽  
Volcanic Eruptions ◽  
Ocean Waves ◽  
The Other ◽  
Tsunami Generation ◽  
Sea Waves ◽  
Tsunami Propagation ◽  
Tidal Waves ◽  
Special Cases

This chapter describes a mathematical model of tsunami propagation (transient waves). A tsunami is a series of ocean waves triggered by large-scale disturbances of the ocean, including earthquakes, as well as landslides, volcanic eruptions, and meteorites. Tsunamis have very long wavelengths (typically hundreds of kilometers). They have also been called “tidal waves” or “seismic sea waves,” but both terms are misleading. The chapter first considers the boundary-value problem before modeling two special cases of tsunami generation, one due to an initial displacement on the free surface and the other due to tilting of the seafloor. It also discusses surface waves on deep water and how fast the wave energy propagates and concludes with an analysis of leading waves due to a transient disturbance.

scholarly journals A mathematical model of a slurry reactor for the direct synthesis of hydrogen peroxide

2019 ◽  
Vol 4 (12) ◽  
pp. 2117-2128 ◽  
Author(s):  
Fabio Pizzetti ◽  
Vittoria M. A. Granata ◽  
Umberto Riva ◽  
Filippo Rossi ◽  
Maurizio Masi
Keyword(s):  
Mathematical Model ◽  
Hydrogen Peroxide ◽  
Large Scale ◽  
Direct Synthesis ◽  
Slurry Reactor ◽  
Global Demand

The direct synthesis of H2O2 is a green alternative to the conventional large-scale anthraquinone process and offers a significantly economic advantageous way of producing a compound for which the global demand is ever increasing.

scholarly journals Simulation study of the large-scale modification of the mid-latitude F-layer by HF radio waves with different powers

2012 ◽  
Vol 30 (8) ◽  
pp. 1213-1222 ◽  
Author(s):  
G. I. Mingaleva ◽  
V. S. Mingalev ◽  
O. V. Mingalev
Keyword(s):  
Mathematical Model ◽  
Simulation Study ◽  
High Power ◽  
Large Scale ◽  
Radio Waves ◽  
Effective Frequency ◽  
Heating Facility ◽  
Absorbed Power

Abstract. A mathematical model of the ionosphere, developed earlier, is applied to investigate the large-scale mid-latitude F-layer modification by HF radio waves with different powers. Simulations are performed for the point with geographic coordinates of the "Sura" heating facility (Nizhny Novgorod, Russia) for autumn conditions. The calculations are made for distinct cases, in which the effective absorbed power has different values belonging to the 5–100 MW range, both for nocturnal and daytime conditions. The frequency of powerful HF waves is chosen to be close to the most effective frequency for the large-scale F2-layer modification. The results of modeling indicate that the effective absorbed power can influence considerably the F-layer response to high-power radio waves in the mid-latitude ionosphere.

Study on the Optimized Cutting Parameters for the Nuclear Channel Head

2011 ◽  
Vol 121-126 ◽  
pp. 3534-3540
Author(s):  
Zhong Hai Yu ◽  
Tian Chen ◽  
Di Shi Liu ◽  
Jing Wang
Keyword(s):  
Mathematical Model ◽  
Nuclear Power ◽  
Large Scale ◽  
Production Efficiency ◽  
Biological Evolution ◽  
Cutting Parameters ◽  
Optimal Combination ◽  
Cnc Machining ◽  
Machining Efficiency ◽  
Complicated Shape

As one of the key components of the nuclear power equipments, the nuclear channel head has a complicated shape and is difficult to be machined. In this paper, the optimal combination of cutting parameters of large-scale nuclear channel head is researched. Considering the machining requirements and machining conditions, the cutting parameters optimized mathematical model is established to achieve the goal of maximum production efficiency. Meanwhile, the target functions and the corresponding constraint functions are analyzed. Finally, by using genetic algorithm of simulating biological evolution, the mathematic models of cutting parameters of CNC machining are compared and optimized. Then the optimized results are compared with the cutting parameters obtained through the trial-producing experience and manual of a small-size channel head. We conclude that the optimized cutting parameters can greatly increase the CNC machining efficiency of Nuclear Channel Head.

DynTriPy: A Python Package for Detecting Dynamic Earthquake Triggering Signals

2020 ◽  
Vol 92 (1) ◽  
pp. 543-554
Author(s):  
Naidan Yun ◽  
Hongfeng Yang ◽  
Shiyong Zhou
Keyword(s):  
Large Scale ◽  
Seismic Analysis ◽  
Parallel Architecture ◽  
Global Scale ◽  
Earthquake Triggering ◽  
Process Data ◽  
Dynamic Triggering ◽  
Earthquake Interaction ◽  
High Level ◽  
Python Package

Abstract Long-term and large-scale observations of dynamic earthquake triggering are urgently needed to understand the mechanism of earthquake interaction and assess seismic hazards. We developed a robust Python package termed DynTriPy to automatically detect dynamic triggering signals by distinguishing anomalous seismicity after the arrival of remote earthquakes. This package is an efficient implementation of the high-frequency power integral ratio algorithm, which is suitable for processing big data independent of earthquake catalogs or subjective judgments and can suppress the influence of noise and variations in the background seismicity. Finally, a confidence level of dynamic triggering (0–1) is statistically yielded. DynTriPy is designed to process data from multiple stations in parallel, taking advantage of rapidly expanding seismic arrays to monitor triggering on a global scale. Various data formats are supported, such as Seismic Analysis Code, mini Standard for Exchange of Earthquake Data (miniSEED), and SEED. To tune parameters more conveniently, we build a function to generate a database that stores power integrals in different time and frequency segments. All calculation functions possess a high-level parallel architecture, thoroughly capitalizing on available computational resources. We output and store the results of each function for continuous operation in the event of an unexpected interruption. The deployment of DynTriPy to data centers for real-time monitoring and investigating the sudden activation of any signal within a certain frequency scope has broad application prospects.

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