- GNS Announces Licensing Deals With MIT, the Institute for Systems Biology and University of Oklahoma -

ITHACA, NY - November 14, 2002 - Gene Network Sciences (GNS) today announced the launch of VisualCell™, a data integration platform and drawing software toolkit that enables large-scale cellular modeling. VisualCell allows biologists and modelers to create detailed drawings of signal transduction pathways and gene expression networks using the GNS Diagrammatic Cell LanguageTM, the first grammatically and mathematically complete language that can compactly represent millions of chemical states and relations.

VisualCell combines one-click cell drawing tools with standard annotations, allowing organizations to display and document heterogeneous data. Protein and mRNA data can be directly overlaid on the diagram and viewed over time. Able to be read by both people and computers, VisualCell provides scalable, precise representations of cellular interactions. Using other GNS technologies, VisualCell diagrams can be automatically parsed into simulation code. In addition, the company is offering Cell NavigatorTM, a library of annotated pathways drawn in VisualCell by GNS biologists, which can be purchased to jump-start or build on existing modeling and pathway description efforts.

Gene Network Sciences also announced that it has signed VisualCell licensing agreements providing proprietary modeling tools and software to MIT, the Institute for Systems Biology and University of Oklahoma. Under the non-exclusive agreements, these organizations will use the GNS Diagrammatic Cell Language and VisualCell software to build large-scale models of biological processes and various diseases.

"GNS has created tools able to capture the complexity of very large models, enabling sophisticated modelers to better visualize and ultimately, better understand cellular interactions," said Nat Goodman, Senior Research Scientist, Institute for Systems Biology. "As more and more genomics and proteomics data become available, it is critical to have a way to turn the deluge of information into a mathematically precise, functional form. The GNS language and VisualCell help incorporate this wealth of data into a robust framework that can power detailed computer simulations of biochemical processes in the context of the cell circuitry."

GNS invites additional non-profit and academic partnerships and is offering deeply discounted VisualCell licenses to the first 50 qualifying groups. The company also welcomes commercial licensees.

"VisualCell provides a way for people within and across organizations to literally speak the same language, creating a standard for the visualization and storage of legacy and incoming data," said Colin Hill, CEO of Gene Network Sciences. "The initial response to our language and VisualCell has been overwhelmingly positive, underscoring the need for a compact, precise method for representing the complexity of biological functions."

In addition to licensing its tools, GNS continues to advance its internal data-driven modeling efforts. Earlier this year, the company announced that it created the largest known computer model of a human cancer cell. GNS built the predictive simulation of a colon cancer cell, which consists of more than 500 genes and proteins, using its VisualCell software and DigitalCellTM platform, along with experimental data points of mRNA, protein, and phosphorylated protein levels. As well as its colon cancer modeling, GNS is working on simulations of additional cancers, E. coli bacteria and Mycoplasma genitalium.

 
About Gene Network Sciences

Founded in August 2000, Gene Network Sciences (www.gnsbiotech.com) is a privately held biotech company headquartered in Ithaca, New York. A pioneer in the field of systems biology, GNS integrates biological and chemical data to create accurate and robust computer models of cell function and human biology. GNS helps pharmaceutical companies better understand the complex human biological systems that they seek to affect. The company's technology will ultimately increase clinical trial success rates and help bring better drugs to market faster.

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