Journal: BMC Bioinformatics

Article Title: Odefy -- From discrete to continuous models

doi: 10.1186/1471-2105-11-233

Figure Lengend Snippet: Odefy overview . Odefy generates models from sets of Boolean equations or Boolean hypergraphs created with yEd. Alternatively, Boolean models can be imported from the CellNetAnalyzer, GINsim or the PBN toolbox. Odefy contains a method for the automatic generation of multi-compartment models from a given single cell model. Boolean models can be exported to other discrete input formats (for the GNA and SQUAD toolboxes), used for Boolean simulations and analysis within Odefy, or they can be converted to systems of ordinary differential equation (ODE). These ODE systems can either be directly simulated and analyzed with Odefy or exported to well-established model formats, including MATLAB script files, SBML, SB Toolbox models and R script files.

Article Snippet: For the Odefy import process, we represent these operators by the MATLAB language-specific operators &&, || and ~, respectively.

Techniques:

Journal: BMC Bioinformatics

Article Title: Odefy -- From discrete to continuous models

doi: 10.1186/1471-2105-11-233

Figure Lengend Snippet: Boolean model definition . A The easiest way to define a Boolean model in Odefy is to specify a set of Boolean equations in a text file. This example represents an asymmetric version of the mutual inhibitory switch shown in the results section. Note the use of the MATLAB language-specific operators &&, || and ~. B Regulatory interaction graph created with the yEd graph editor. Regular arrows represent activatory influences whereas diamond-head arrows stand for inhibition. Note that we need to specify a generic logic to combine multiple regulatory inputs for node E . The Odefy default at least one activator and no inhibitors logic would result in E = ( A ∨ C ) ˄ ¬ ( B ∨ C ). C Alternative representation of the Boolean model as a hypergraph. Using a specialized node '&' we can precisely specify the Boolean logic for node E . All edges not incident to a '&' node are treated with an OR logic. The resulting Boolean update rule reads E = ( A ˄ ¬ B ) ∨ C ∨ ¬ D . ˄ = logical AND, ∨ = logical OR, ¬ = logical NOT.

Article Snippet: For the Odefy import process, we represent these operators by the MATLAB language-specific operators &&, || and ~, respectively.

Techniques: Inhibition

Journal: BMC Bioinformatics

Article Title: Odefy -- From discrete to continuous models

doi: 10.1186/1471-2105-11-233

Figure Lengend Snippet: Odefy overview . Odefy generates models from sets of Boolean equations or Boolean hypergraphs created with yEd. Alternatively, Boolean models can be imported from the CellNetAnalyzer, GINsim or the PBN toolbox. Odefy contains a method for the automatic generation of multi-compartment models from a given single cell model. Boolean models can be exported to other discrete input formats (for the GNA and SQUAD toolboxes), used for Boolean simulations and analysis within Odefy, or they can be converted to systems of ordinary differential equation (ODE). These ODE systems can either be directly simulated and analyzed with Odefy or exported to well-established model formats, including MATLAB script files, SBML, SB Toolbox models and R script files.

Article Snippet: We present Odefy , a MATLAB- and Octave-compatible toolbox for the automated transformation of Boolean models into systems of ordinary differential equations.

Techniques:

Journal: BMC Bioinformatics

Article Title: Odefy -- From discrete to continuous models

doi: 10.1186/1471-2105-11-233

Figure Lengend Snippet: Boolean model definition . A The easiest way to define a Boolean model in Odefy is to specify a set of Boolean equations in a text file. This example represents an asymmetric version of the mutual inhibitory switch shown in the results section. Note the use of the MATLAB language-specific operators &&, || and ~. B Regulatory interaction graph created with the yEd graph editor. Regular arrows represent activatory influences whereas diamond-head arrows stand for inhibition. Note that we need to specify a generic logic to combine multiple regulatory inputs for node E . The Odefy default at least one activator and no inhibitors logic would result in E = ( A ∨ C ) ˄ ¬ ( B ∨ C ). C Alternative representation of the Boolean model as a hypergraph. Using a specialized node '&' we can precisely specify the Boolean logic for node E . All edges not incident to a '&' node are treated with an OR logic. The resulting Boolean update rule reads E = ( A ˄ ¬ B ) ∨ C ∨ ¬ D . ˄ = logical AND, ∨ = logical OR, ¬ = logical NOT.

Article Snippet: We present Odefy , a MATLAB- and Octave-compatible toolbox for the automated transformation of Boolean models into systems of ordinary differential equations.

Techniques: Inhibition

Journal: BMC Bioinformatics

Article Title: Odefy -- From discrete to continuous models

doi: 10.1186/1471-2105-11-233

Figure Lengend Snippet: Continuous homologues of Boolean functions . Continuous homologues of Boolean functions. A Multilinear interpolation of a two-variable OR gate (Boole-Cube). B Hill functions with Hill coefficients n = 2, 4, 8, 16 and k = 0.5 as continuous relaxation of a Boolean step function. C Composition of BooleCube from (A) with Hill functions (HillCube). D normalized HillCube from (C).

Article Snippet: Here we present a user-friendly implementation of the HillCube technique suitable for large-scale networks in a MATLAB/Octave toolbox called Odefy .

Techniques: