The National Human Genome Research Institute has awarded nearly $9 million in bioinformatics-related grants in fiscal year 2012 as part of a $30 million effort to expand the Encyclopedia of DNA Elements, or ENCODE, project.
The effort, which recently published several dozen papers in Nature, Science, Genome Research, Genome Biology, and elsewhere, aims to catalog all the functional gene regulatory elements in the human genome.
The new round of grants issued this week will fund seven ENCODE data-production centers, which are responsible for mapping various regulatory elements. On the informatics side, the new funding will support a data coordination center, a data analysis center, and six computational analysis projects.
The informatics awards are as follows:
The Stanford group will work with the data production centers to "collect, organize, and store" ENCODE data, and provide researchers with access to data from the project.
According to the grant abstract, the DCC "will construct a state-of-the-art data storage repository called the Big Data Hub" and will develop new software to "enhance the data submission and processing pipeline, the organization and access to metadata and the Big Data Hub."
The Stanford team will also create an ENCODE Portal that will be the "primary entry point" to data generated for the project — both experimentally determined information and the results of computational analyses.
This group will work with the data production centers to perform "integrated analyses" of ENCODE data, and to make it easier for researchers to use the data.
The grant abstract states that the DAC will work with the ENCODE Analysis Working Group to "define and prioritize integrative analyses of ENCODE data." The center will also provide shared computational guidelines and infrastructure; carry out data integration, exploratory data analyses, and comparative analyses; and facilitate integration with the genome-wide association studies community and disease datasets.
ENCODE Computational Analysis Awards
Bickel's group will develop statistical and computational approaches to reduce the complexity of ENCODE data and enable comparisons of many ENCODE datasets at once.
The MIT team will develop computational methods to identify regulatory elements in ENCODE data, and to learn how components within each regulatory element work together.
This group will develop statistical methods and software to identify regulatory elements in the human genome, particularly in sequences that are repeated at several locations.
Klein's team will develop computational approaches that use ENCODE data to identify cell types and genetic changes responsible for human disease.
The University of Chicago group will develop computational methods to determine how changes in DNA sequence lead to changes in gene expression.
The UCLA team will identify genetic differences that alter RNA processing.