Cell Signaling Classification System Gives Researchers New Tool

Using ever-growing genome data, scientists with the Department of Energy's (DOE) Oak Ridge National Laboratory and the University of Tennessee are tracing the evolution of the bacterial regulatory system that controls cellular motility, potentially giving researchers a method for predicting important cellular functions that will impact both medical and biotechnology research.

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Using ever-growing genome data, scientists with the Department of Energy's (DOE) Oak Ridge National Laboratory and the University of Tennessee are tracing the evolution of the bacterial regulatory system that controls cellular motility, potentially giving researchers a method for predicting important cellular functions that will impact both medical and biotechnology research.

A new study from the Joint Institute for Computational Sciences, a research venture between ORNL and UT, has demonstrated how knowledge of biological systems can be derived by computational interrogation of genomic sequences. The results have implications for areas ranging from medicine to bioenergy.

"We now have hundreds of millions of DNA sequences from all sorts of organisms deposited in databases. However, our abilities to translate raw genomic data into useful knowledge are still very limited," said Igor Zhulin, joint faculty professor and principal investigator.

"We applied our computational skills to glean more information about a biological system that has fascinated researchers for more than a century. This is a molecular signal transduction system that allows bacteria to navigate in the environment pretty much in the same way that higher organisms, including humans, do—by detecting signals (e.g. visual or chemical cues) and then moving toward favorable environments and away from dangerous ones."

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