Cells Are Like Robust Computational Systems, Scientists Report

Gene regulatory networks in cell nuclei are similar to cloud computing networks, such as Google or Yahoo!, researchers report today in the online journal Molecular Systems Biology. The similarity is that each system keeps working despite the failure of individual components, whether they are master genes or computer processors.

This finding by an international team led by Carnegie Mellon University computational biologist Ziv Bar-Joseph helps explain not only the robustness of cells, but also some seemingly incongruent experimental results that have puzzled biologists.

“Similarities in the sequences of certain master genes allow them to back up each other to a degree we hadn’t appreciated,” said Bar-Joseph, an assistant professor of computer science and machine learning and a member of Carnegie Mellon’s Ray and Stephanie Lane Center for Computational Biology.

Between 5 and 10 percent of the genes in all living species are master genes that produce proteins called transcription factors that turn all other genes on or off. Many diseases are associated with mutations in one or several of these transcription factors. However, as the new study shows, if one of these genes is lost, other “parallel” master genes with similar sequences, called paralogs, often can replace it by turning on the same set of genes.

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