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Evolutionary information improves discovery of mutations associated with diseases

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TechAndComputer (July 17, 2012) — A book containing misprints may cause annoyance for the reader, but typos in an individual's genetic blueprint (DNA) can mean serious disease or even death. The search for genetic correlates for the wide range of diseases plaguing humankind has inspired a wealth of research falling under the heading of genome-wide association studies (GWAS).

According to Sudhir Kumar, director of the Center for Evolutionary Medicine and Informatics at Arizona State University's Biodesign Institute, however, results from many such studies become less useful when gene variants or alleles implicated in disease in a given population fail to be discovered in subsequent independent studies. "Often, we do not...

New tools facilitate matching cancer drugs with gene targets

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TechAndComputer (July 16, 2012) — A new study details how a suite of web-based tools provides the research community with greatly improved capacity to compare data derived from large collections of genomic information against thousands of drugs. By comparing drugs and genetic targets, researchers can more easily identify pharmaceuticals that could be effective against different forms of cancer.

The newly updated software, called CellMiner, was built for use with the NCI-60, one...

Searching genomic data faster: Biologists' capacity for generating genomic data is increasing more rapidly than computing power

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TechAndComputer (July 10, 2012) — In 2001, the Human Genome Project and Celera Genomics announced that after 10 years of work at a cost of some $400 million, they had completed a draft sequence of the human genome. Today, sequencing a human genome is something that a single researcher can do in a couple of weeks for less than $10,000.

Since 2002, the rate at which genomes can be sequenced has been doubling every four months or so, whereas computing power doubles only every 18...

Molecular matchmaking for drug discovery

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TechAndComputer (June 5, 2012) — For millennia, humankind has discovered new drugs either through educated guesswork or blind luck. But with the proliferation of advanced computing, a new paradigm has emerged whereby one can find drug targets through simulation and modeling.

Chandrajit Bajaj, professor of computer science at The University of Texas at Austin has been integrally involved in these efforts for more than 20 years. Computational and Applied Mathematics chair in...

Google goes cancer: Search engine algorithm finds cancer biomarkers

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TechAndComputer (May 17, 2012) — The strategy used by Google to decide which pages are relevant for a search query can also be used to determine which proteins in a patient's cancer are relevant for the disease progression. Researchers from Dresden University of Technology, Germany, have used a modified version of Google's PageRank algorithm to rank about 20,000 proteins by their genetic relevance to the progression of pancreatic cancer. In their study, published in PLoS Computational...