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StikChops - the eating utensil for all

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M i c h e l I n a
Design Development
F o r m W o r k s
Studio
5358 Kilbourne Drive
Cleveland Ohio 44124
T. 216 361 9278
M.  216 526 0676
www.michel-ina.com
michel@michel-ina.com
Photography: Michel Ina

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Talk given at the Southern California Systems Biology Conference on January 31, 2015 entitled, "GRNmap and GRNsight: Open Source Software for Dynamical Systems Modeling and Visualization of Medium-Scale Gene Regulatory Networks". Abstract: A gene regulatory network (GRN) consists of genes, transcription factors, and the regulatory connections between them that govern the level of expression of mRNA and proteins from those genes. Our group has developed a MATLAB software package, called GRNmap, that uses ordinary differential equations to model the dynamics of medium-scale GRNs. The program uses a penalized least squares approach to estimate production rates, expression thresholds, and regulatory weights for each transcription factor in the network based on gene expression data, and then performs a forward simulation of the dynamics of the network. Parameters for a 21-gene network were optimized against DNA microarray data measuring the transcriptional response to cold shock in wild type and four transcription factor deletion strains of budding yeast, Saccharomyces cerevisiae. Model predictions fit experimental data well, within the 95% confidence interval. Open source code and a compiled executable that can run without a MATLAB license are available from <http: />. GRNsight is an open source web application for visualizing such models of gene regulatory networks. GRNsight accepts GRNmap- or user-generated spreadsheets containing an adjacency matrix representation of the GRN and automatically lays out the graph of the GRN model. The application colors the edges and adjusts their thicknesses based on the sign (activation or repression) and the strength (magnitude) of the regulatory relationship, respectively. Users can then modify the graph to define the best visual layout for the network. The GRNsight code and application are available from <http: />. This work was partially supported by NSF award 0921038.

Dahlquist so calsysbio_20140131

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Southwick anguiano lmu-symposium_presentation_20140329

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Talk and poster presented at the American Society for Biochemistry and Molecular Biology/Experimental Biology Conference on April 4, 2016. Abstract: A gene regulatory network (GRN) consists of genes, transcription factors, and the regulatory connections between them that govern the level of expression of mRNA and proteins from those genes. Our group has developed a MATLAB software package, called GRNmap, that uses ordinary differential equations to model the dynamics of medium-scale GRNs. The program uses a penalized least squares approach (Dahlquist et al. 2015, DOI: 10.1007/s11538-015-0092-6) to estimate production rates, expression thresholds, and regulatory weights for each transcription factor in the network based on gene expression data, and then performs a forward simulation of the dynamics of the network. GRNmap has options for using a sigmoidal or Michaelis-Menten production function. Parameters for a series of related networks, ranging in size from 15 to 35 genes, were optimized against DNA microarray data measuring the transcriptional response to cold shock in wild type and five strains individually deleted for the transcription factors, Cin5, Gln3, Hap4, Hmo1, Zap1, of budding yeast, Saccharomyces cerevisiae BY4741. Model predictions fit the experimental data well, within the 95% confidence interval. Open source code and a compiled executable that can run without a MATLAB license are available from http://kdahlquist.github.io/GRNmap/. GRNsight is an open source web application for visualizing such models of gene regulatory networks. GRNsight accepts GRNmap- or user-generated spreadsheets containing an adjacency matrix representation of the GRN and automatically lays out the graph of the GRN model. The application colors the edges and adjusts their thicknesses based on the sign (activation or repression) and the strength (magnitude) of the regulatory relationship, respectively. Users can then modify the graph to define the best visual layout for the network. The GRNsight open source code and application are available from http://dondi.github.io/GRNsight/index.html.

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Dahlquist so calsysbio_20140131

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StikChops

1. mi 2014 StikChops™ U.S.Pat.8672377

2. 01 U.S.Pat.8672377

3. 02 U.S.Pat.8672377

4. 03U.S. Pat. 8672377

5. 04U.S. Pat. 8672377

6. 05 U.S.Pat.8672377

7. 06U.S. Pat. 8672377

8. 07U.S. Pat. 8672377

9. 08U.S. Pat. 8672377

10. 09U.S. Pat. 8672377

11. 10U.S. Pat. 8672377

12. 11 U.S.Pat.8672377

13. 12U.S. Pat. 8672377

14. 13U.S. Pat. 8672377

15. 14 U.S.Pat.8672377

16. 15U.S. Pat. 8672377

17. 16 U.S.Pat.8672377

18. 17U.S. Pat. 8672377

19. M i c h e l I n a Design Development F o r m W o r k s Studio 5358 Kilbourne Drive Cleveland Ohio 44124 T. 216 361 9278 M.  216 526 0676 www.michel-ina.com michel@michel-ina.com Photography: Michel Ina

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