Here I describe how to use Ingeneue, a software tool for constructing, simulating, and exploring models of gene regulatory networks. Ingeneue is an open source, extensible Java application that allows users to rapidly build ordinary differential equation models of a gene regulatory network without requiring extensive programming or mathematical skills. Models can be in a single cell or 2D sheet of cells, and Ingeneue is well suited for simulating both oscillatory and pattern forming networks. Ingeneue provides features to allow rapid model construction and debugging, sophisticated visualization and statistical tools for model exploration, and a powerful framework for searching parameter space for desired behavior. This chapter provides an overview of the mathematical theory and operation of Ingeneue, and detailed walkthroughs demonstrating how to use the main features and how to construct networks in Ingeneue.
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http://dx.doi.org/10.1007/978-1-59745-525-1_6 | DOI Listing |
Methods Mol Biol
May 2009
Center for Cell Dynamics, University of Washington Friday Harbor Laboratories, 98250, USA.
Here I describe how to use Ingeneue, a software tool for constructing, simulating, and exploring models of gene regulatory networks. Ingeneue is an open source, extensible Java application that allows users to rapidly build ordinary differential equation models of a gene regulatory network without requiring extensive programming or mathematical skills. Models can be in a single cell or 2D sheet of cells, and Ingeneue is well suited for simulating both oscillatory and pattern forming networks.
View Article and Find Full Text PDFJ Exp Zool
October 2002
Department of Zoology, University of Washington, Seattle, Washington 98105, USA.
Here we describe a software tool for synthesizing molecular genetic data into models of genetic networks. Our software program Ingeneue, written in Java, lets the user quickly turn a map of a genetic network into a dynamical model consisting of a set of ordinary differential equations. We developed Ingeneue as part of an ongoing effort to explore the design and evolvability of genetic networks.
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