( On any given day tens of thousands of ...)Drawing with DNA: 'Bioart' illuminates genomics

On any given day, tens of thousands of biologists around the globe run DNA sequences of unknown function through a lightning-fast online algorithm called BLAST ?typically submitting 200 to 400 base pairs, or "letters" of genetic code, to be matched against the billions of letters for known genes. Searching for similarities that can shed light on functional or evolutionary relationships, scientists routinely use BLAST to churn through and produce vast amounts of data. Everyday applications include genetic medicine and pharmaceuticals. Yet this process and, more generally, genomics remain dimly understood by the public.

"Ecce Homology," an interactive "bioart" installation to be showcased at SIGGRAPH 2005 ?in Los Angeles, July 31 through Aug. 4 ?quite literally makes BLAST and genomics visible.

Headed up by new-media artist Ruth West ?director of visual analytics and interactive technologies at the University of California, San Diego National Center for Microscopy and Imaging Research and research associate with the UCSD Center for Research and Computing in the Arts ?the "Ecce Homology" project is an ongoing collaboration among 11 biologists, artists and computer scientists from UCSD, UCLA and the University of Southern California.

Named after Friedrich Nietzsche's Ecce Homo, a meditation on how one becomes what one is, the project explores human evolution by examining similarities ?a.k.a. "homology" ?between genes from human beings and a target organism, in this case the rice plant.

"We are living in a time when we are generating enormous amounts of genetic data," said West, who trained as a microbiologist and began her career in medical genetics. "But data is not knowledge ?it's not even information. A key concept of 'Ecce Homology' is to make an important subject like genomics accessible to the general public."

"Ecce Homology" uses a combination of dynamic media, computer vision and computer graphics to visualize genomic data.
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Source:University of California - San Diego

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