Messages in the Noise

After spending more than a decade developing tools to study patterns in gene sequences, bioinformaticians are now working on programs to analyze epigenomics data.

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CLUSTER KLATCHES: Using A-Clustering to analyze 28 spots on a human genome revealed clusters of sites (in yellow) that follow similar methylation patterns. Changing the program’s parameters by dictating how large or close together sites can be slightly altered the identification of the clusters. TAMAR SOFER, UNIVERSITY OF WASHINGTON

Just a decade ago, epigenetics researchers used classic biochemistry to reveal key modifications involved in the control of gene expression. These days, discoveries in epigenetics are as likely to be made with a computer as they are to rely on freezers full of cells or stacks of petri dishes. Researchers working to understand the intricacies of methylation marks, histone patterns, and chromosome structure must use computational approaches.

“Given the way the field is moving, if you do high-throughput experiments of any kind, whether they’re genetic or epigenetic, computation is just part of the pipeline,” says William Noble, a professor of genome sciences and of computer science at the University of Washington School of Medicine, and one of the computer-scientists-turned-epigeneticists who are developing new tools—and making ...

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