Industries

Overview and Challenges

Recent research in genetics has generated vast quantities of information that has the potential to dramatically accelerate the research and development process in the health care and pharmaceutical industries. For example, every organism has a unique protein-to-protein interaction network. If pharmaceutical researchers can understand the pathways through these networks, they can target drug treatments at specific protein-to-protein interactions. Unlike traditional approaches, this kind of treatment development can lead to products that attack a disease at its root rather than simply treating its symptoms.

Along with the human genome project's identification of more than 30,000 human genes comes the awareness that sequencing genes is only the beginning. Researchers now face the difficult task of understanding how these genes interact with one another in complex networks. Applications using Tom Sawyer's sophisticated graph layout technology can produce diagrams that clearly show the relationships between this complex data.

Tom Sawyer Software Solutions

Tom Sawyer's graph layout and diagramming technologies are perfectly suited for modeling, analyzing, and visualizing metabolic signaling pathways and regulatory networks. Our nested drawing technology is both general and flexible, and it easily adapts to represent complicated biological systems models. Our automatic graph layout facilities can also be used to depict cellular and chemical reactions as extensive yet clear and easy-to-understand diagrams.

Tom Sawyer is currently working with a growing number of forward-looking companies and research institutions including Affymetrix, Basel Institute, Berlex Biosciences, European Bioinformatics Institute, GlaxoSmithKline, Harvard University Medical School, Merck, Princeton University and the University of Washington.

The life sciences application of Tom Sawyer products helps today's pharmaceutical researchers enhance their research, dramatically reducing the time and cost required to develop new products.

This hierarchical drawing illustrates the British royal family tree and indicates the prevalence of hemophilia throughout the generations.

This orthogonal graph drawing represents the metabolic pathway for inositol metabolism.

This hierarchical graph drawing represents the metabolic pathway for lipopolysaccharide metabolism.

Case Study

• See our Bilkent Center for Bioinformatics Case Study.