caBIG™ Awarded Bio-IT World’s Editor’s Choice Award
The cancer Biomedical Informatics Grid™ (caBIG™) initiative was recently honored as the sole winner of Bio-IT World’s prestigious Editor’s Choice Award 2008, for the implementation of an open source network to speed cancer research.
Kenneth H. Buetow, Ph.D., associate director for Bioinformatics and Information Technology at the National Cancer Institute (NCI) accepted the award on behalf of caBIG™ at Bio-IT World’s Best Practices Awards Dinner on April 29, 2008, which was held in conjunction with the Sixth Annual Bio-IT World Conference and Expo.
"The caBIG™ initiative has been the result of dedicated efforts on the part of more than 1,000 individuals from more than 200 academic, government, and commercial organizations across the country over the past four years," Dr. Buetow said. Read more
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Access to Genetic Variants Speeds Disease Research
The 21st century has seen great progress in our understanding of common, complex diseases such as cancer, heart disease, and diabetes through the application of genomic and genetic information gained from large-scale research initiatives, including the Human Genome Project and the International HapMap Project. Such projects have opened the door to faster and more effective diagnostic and therapeutic agents, and the pace of discovery is accelerating. High-throughput technologies promise to double the amount of biological information available to researchers every 12–18 months, with no end in sight.
Researchers are now conducting genome-wide association studies (GWAS) to scan the genomes of thousands of individuals, looking for single nucleotide polymorphisms (SNPs), common genetic variations that may be associated with specific diseases. As GWAS technology becomes increasingly efficient, researchers are challenged to meaningfully integrate and transform the wealth of genetic association data into better strategies to diagnose, treat, and even prevent disease.
To simplify the process of accessing and sharing GWAS data, the National Cancer Institute Center for Bioinformatics and Information Technology (NCI-CBIIT) developed Cancer Genome-Wide Association Studies (caGWAS), a model GWAS management system that allows researchers to share, integrate, query, and analyze associations between genetic variations and diseases, finding these associations more quickly than any prior analytical approach.
"It is only in the last couple of years that we’ve had the ability to mine the entire genome for hundreds of thousands of variants," said Subha Madhavan, Ph.D., associate director, Products & Programs at the NCI-CBIIT. "The caGWAS model is helping investigators to search and retrieve the needle in the haystack." Read more
