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Baroreflex mechanism as a model for integration of genotype, phenotype, computational model, and pathway information within a user‐friendly graphical interface
Abstract only Translational research requires effective integration of physiological and genomic data with informative predictive modeling. Our goal was to develop a tool that would allow physiology, genetics, and computational biology researchers to explore existing data and models within an intuit...
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Published in: | The FASEB journal 2013-04, Vol.27 (S1) |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Online Access: | Get full text |
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Summary: | Abstract only Translational research requires effective integration of physiological and genomic data with informative predictive modeling. Our goal was to develop a tool that would allow physiology, genetics, and computational biology researchers to explore existing data and models within an intuitive pathway framework that allows logical integration of multiple, diverse datasets with physiological processes and mathematical equations developed to describe them.
A multi‐level diagram depicting the baroreflex mechanism was created using a program designed for the Rat Genome Database (
www.rgd.mcw.edu
) to model physiological pathways. The diagram was integrated with a well‐established baroreceptor model (Bugenhagen, et al, 2010). Images were imported, linked and labeled to identify various components of the process. Processes were linked to multiple datasets, genomic information, and computational model equations. Weekly meetings with physiologists, bioinformaticians, and computational physiologists elucidated the challenges in creating the model and established effective guidelines for enhancement of the tool. Additional communication with the graphical design artist and software developer allowed for refinement of the image quality and improvement in the ease of use and functionality of the tool.
Funding was made possible by NIH HL64541 (RGD) and the APS Frontiers in Physiology program. |
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ISSN: | 0892-6638 1530-6860 |
DOI: | 10.1096/fasebj.27.1_supplement.lb853 |