NIH pumping $23M into data center and computer analyses of genomes

An eight-year-old project to uncover the mysteries of the human genome got a big shot in the arm this week. An NIH advisory council approved some $153 million in new funding for four programs to expand the Encyclopedia of DNA Elements (ENCODE). These programs might help us get a better handle on what the tsunami of genomic data generated from sequencers really means.

For FierceBiotech IT readers, particularly informatics folks, two of the newly endorsed programs should be of particular interest. The National Advisory Council for Human Genome Research approved $14 million to be spent over four years on a data analysis and coordination center, which will include a centralized database for all ENCODE projects. Also, the advisory group consented to $9 million in funding over the next three years for computational analyses of genomic data, aiming to glean new biological insights from the genomic information, according to documents from the National Human Genome Research Institute (NHGRI), which is the NIH institute that oversees ENCODE.

The ENCODE project grew from a modest endeavor launched in 2003 to study 1 percent of the human genome to a multinational effort to understand the entire human genome in 2007. While it was a huge feat to sequence an entire human genome about a decade ago, perhaps an even bigger task will be expanding our knowledge of how the genome functions. Computational analysis of the raw data generated from DNA sequencers is thought to be one way to deepen our understanding of the genome, making it easier to identify, say, a gene or network of genes driving diseases.

"Once we had the human genome sequenced, we really didn't know how to read the sequence, we didn't have what I like to call an instruction manual," Elise Feingold, program director of genome analysis at the NHGRI, tells FierceBiotech IT. "So we are trying to actually functionalize the human genome and annotate it as best as we can" with the ENCODE projects.

- read more in this GenomeWeb report (sub. req.)

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