ANN ARBOR, Mich. Looking for answers in the bright light of day, rather than the confined beam of a street light at night. Thats how University of Michigan researcher Sofia Merajver, M.D., Ph.D., describes the power of a new mathematical model that could have far-reaching impact on how scientists study cellular signaling pathways.
This has the potential to be a true paradigm shift, says Merajver, a professor in the U-M Department of Internal Medicine and co-director of the Breast Oncology Program at the U-M Comprehensive Cancer Center. She is the senior author of a study about the new model published online March 21 in Plos Computational Biology.
Around the world, researchers scrutinize the pathways inside cells where signals travel and activate or suppress thousands of cell functions. The researchers want to learn which cellular processes are key in causing disease conditions and how to target them with new drugs. Understanding the full complexity of signaling pathways and their interactions is critical in discovering effective treatments for cancer, inflammation and other conditions that affect millions of people.
The full description of the new model in the article immediately offers scientists the opportunity to improve current mathematical models with a superior tool that can take advantage of advances in computing power, says Merajver.
I would hope that it may help guide us much better than our own intuition to decide what our targets are, she says. If we can understand these pathways better, we should be able to pick more effective targets. This is the step before screening a drug. Until now, there have been very few tools to help us choose a target.
Merajvers collaborators in the study are first author Alejandra C. Ventura, Ph.D., a post-doctoral fellow in the U-M Department of Internal Medicine, Division of Hematology and Oncology and Comprehensive Cancer Center; and Jacques-A. Sepulchre, a mathematic
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