DIZZY: STOCHASTIC SIMULATION OF LARGE-SCALE GENETIC REGULATORY NETWORKS

2005 ◽  
Vol 03 (02) ◽  
pp. 415-436 ◽  
Author(s):  
STEPHEN RAMSEY ◽  
DAVID ORRELL ◽  
HAMID BOLOURI
Keyword(s):  
Regulatory Networks ◽  
Large Scale ◽  
Software Tool ◽  
Genetic Regulatory Networks ◽  
Signaling Networks ◽  
Simulation Framework ◽  
Kinetic Rate ◽  
Rate Laws ◽  
Reaction Processes ◽  
Kinetics Of

We describe Dizzy, a software tool for stochastically and deterministically modeling the spatially homogeneous kinetics of integrated large-scale genetic, metabolic, and signaling networks. Notable features include a modular simulation framework, reusable modeling elements, complex kinetic rate laws, multi-step reaction processes, steady-state noise estimation, and spatial compartmentalization.

scholarly journals OCSANA+: Optimal Control and Simulation of Signaling Networks from Network Analysis

2019 ◽  
Author(s):  
Lauren Marazzi ◽  
Andrew Gainer-Dewar ◽  
Paola Vera-Licona
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Software Tool ◽  
Control Algorithms ◽  
Signaling Networks ◽  
Analysis Software ◽  
Link Type ◽  
Non Linear Systems ◽  
Long Term Behavior

AbstractSummaryOCSANA+ is a Cytoscape app for identifying nodes to drive the system towards a desired long-term behavior, prioritizing combinations of interventions in large scale complex networks, and estimating the effects of node perturbations in signaling networks, all based on the analysis of the network’s structure. OCSANA+ includes an update to OCSANA (optimal combinations of interventions from network analysis) software tool with cutting-edge and rigorously tested algorithms, together with recently-developed structure-based control algorithms for non-linear systems and an algorithm for estimating signal flow. All these algorithms are based on the network’s topology. OCSANA+ is implemented as a Cytoscape app to enable a user interface for running analyses and visualizing results.Availability and ImplementationOCSANA+ app and its tutorial can be downloaded from the Cytoscape App Store or https://veraliconaresearchgroup.github.io/OCSANA-Plus/. The source code and computations are available in https://github.com/VeraLiconaResearchGroup/OCSANA-Plus_SourceCode.

scholarly journals OCSANA+: optimal control and simulation of signaling networks from network analysis

2020 ◽  
Vol 36 (19) ◽  
pp. 4960-4962
Author(s):  
Lauren Marazzi ◽  
Andrew Gainer-Dewar ◽  
Paola Vera-Licona
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Software Tool ◽  
Supplementary Information ◽  
Control Algorithms ◽  
Signaling Networks ◽  
Analysis Software ◽  
Non Linear Systems ◽  
Long Term Behavior

Abstract Summary OCSANA+ is a Cytoscape app for identifying nodes to drive the system toward a desired long-term behavior, prioritizing combinations of interventions in large-scale complex networks, and estimating the effects of node perturbations in signaling networks, all based on the analysis of the network’s structure. OCSANA+ includes an update to optimal combinations of interventions from network analysis software tool with cutting-edge and rigorously tested algorithms, together with recently developed structure-based control algorithms for non-linear systems and an algorithm for estimating signal flow. All these algorithms are based on the network’s topology. OCSANA+ is implemented as a Cytoscape app to enable a user interface for running analyses and visualizing results. Availability and implementation OCSANA+ app and its tutorial can be downloaded from the Cytoscape App Store or https://veraliconaresearchgroup.github.io/OCSANA-Plus/. The source code and computations are available in https://github.com/VeraLiconaResearchGroup/OCSANA-Plus_SourceCode. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Wepy: A Flexible Software Framework for Simulating Rare Events with Weighted Ensemble Resampling

2020 ◽  
Author(s):  
Samuel Lotz ◽  
Alex Dickson
Keyword(s):  
Conformational Changes ◽  
Large Scale ◽  
Modular Design ◽  
Software Tool ◽  
Software Framework ◽  
Simulation Framework ◽  
Domain Experts ◽  
Full Support ◽  
Molecular Events ◽  
Python Package

This paper describes the software tool "wepy", an implementation of the weighted ensemble algorithm in python. Wepy was designed to be a flexible simulation framework for rare or long-timescale molecular events, such as protein (un)folding, ligand (un)binding, and large-scale conformational changes or rearrangements. It is implemented as a pure python package, which works well with the OpenMM python library and can easily leverage other python tools for that are useful for molecular simulation and analysis such as mdtraj, scikit-learn, numpy and scipy. It has full support for high-dimensional adaptive resampling algorithms (WExplore and REVO) and provides a framework to easily facilitate the development of new resampling algorithms. Its modular design allows domain experts to write their own analysis functions and progress variables, while taking advantage of a vetted framework for parallel simulation and weighted ensemble resampling.

scholarly journals MODELING OF ESSENTIAL OIL EXTRACTION PROCESS: APPLICATION FOR ORANGE, POMELO, AND LEMONGRASS

2018 ◽  
Vol 56 (4A) ◽  
pp. 182
Author(s):  
Thanh Nguyen Dang Binh ◽  
Dung Nguyen Trung ◽  
Duc Hong Ta
Keyword(s):  
Large Scale ◽  
Scale Up ◽  
Extraction Process ◽  
Model Parameters ◽  
Two Stage ◽  
Kinetic Rate ◽  
Kinetic Mechanisms ◽  
Extraction Processes ◽  
Solid Liquid ◽  
Kinetics Of

ABSTRACT - HCTN - 44In this study, the kinetic models of steam distillation of orange (Citrus Sinensis (L.) Osbeck), pomelo (Citrus grandis L.), and lemongrass (Cymbopogon Citratus) for the recovery of essential oils were developed. The model parameters were estimated based on experimental data and comprehensive kinetic mechanisms of the solid-liquid extraction process. Numerical results showed that, the extraction mechanism of the three materials were best fit to the Patricelli two-stage model in which the diffusion of the oil was followed by the washing step. Moreover, the model parameters obtained from the measured data reflected clearly the nature of the two-stage extraction at which the kinetic rate of the washing step (surface extraction) was higher than that of in-tissue diffusion step. Thus, the kinetics of the extraction processes obtained from the present work could be used for the scale-up of the extraction process operating at a large scale and for the purpose of process control as well.

scholarly journals Genevestigator V3: A Reference Expression Database for the Meta-Analysis of Transcriptomes

2008 ◽  
Vol 2008 ◽  
pp. 1-5 ◽  
Author(s):  
Tomas Hruz ◽  
Oliver Laule ◽  
Gabor Szabo ◽  
Frans Wessendorp ◽  
Stefan Bleuler ◽  
...  
Keyword(s):  
Data Storage ◽  
Regulatory Networks ◽  
Large Scale ◽  
Meta Analysis ◽  
Software Tool ◽  
Manual Curation ◽  
Discovery Research ◽  
Expression Of Genes ◽  
Computationally Intensive ◽  
Analysis System

The Web-based software tool Genevestigator provides powerful tools for biologists to explore gene expression across a wide variety of biological contexts. Its first releases, however, were limited by the scaling ability of the system architecture, multiorganism data storage and analysis capability, and availability of computationally intensive analysis methods. Genevestigator V3 is a novel meta-analysis system resulting from new algorithmic and software development using a client/server architecture, large-scale manual curation and quality control of microarray data for several organisms, and curation of pathway data for mouse and Arabidopsis. In addition to improved querying features, Genevestigator V3 provides new tools to analyze the expression of genes in many different contexts, to identify biomarker genes, to cluster genes into expression modules, and to model expression responses in the context of metabolic and regulatory networks. Being a reference expression database with user-friendly tools, Genevestigator V3 facilitates discovery research and hypothesis validation.

Kinetic Reaction Paths

1996 ◽  
Author(s):  
Craig M. Bethke
Keyword(s):  
Kinetic Data ◽  
Reaction Model ◽  
Laboratory Measurements ◽  
Reaction Paths ◽  
Kinetic Rate ◽  
Dimensionless Variable ◽  
Kinetic Reaction ◽  
Rate Laws ◽  
Calculation Results ◽  
Reaction Processes

In calculating most of the reaction paths in this book, we have measured reaction progress with respect to the dimensionless variable ξ. We showed in Chapter 14, however, that by incorporating kinetic rate laws into a reaction model, we can trace reaction paths using time as the reaction coordinate. In this chapter we construct a variety of kinetic reaction paths to explore how this class of models behaves. Our calculations in each case are based on kinetic rate laws determined by laboratory experiment. In considering the calculation results, therefore, it is important to keep in mind the uncertainties entailed in applying laboratory measurements to model reaction processes in nature, as discussed in detail in Section 14.2. In Chapter 14 we considered how quickly quartz dissolves into water at 100°C, using a kinetic rate law determined by Rimstidt and Barnes (1980). In this section we take up the reaction of silica (SiO2) minerals in more detail, this time working at 25°C. We use kinetic data for quartz and cristobalite from the same study, as shown in Table 20.1.

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