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Showing posts with the label clustering

FPGA-based systems – a very specialized programming skill that many bioinformatics developers don’t have

An “ecosystem” of partners who will use programmable hardware to create a standardized approach for analyzing data from second-generation sequencing instruments. Intel Seeks Partners to Develop FPGA-Based Solution for Next-Gen Sequencing Analysis . “Primary data analysis seems to be where Intel can play the most useful role” in the field, considering the initial analytical steps in sequencing: image processing, base calling, and alignment and assembly. One downside to this scenario, however, is that these codes would need to be written for FPGA-based systems – a very specialized programming skill that many bioinformatics developers don’t have. This challenge could present an opportunity for companies that develop FPGA-based algorithms and software-development toolkits. While the task of harvesting data from second-generation sequencing instruments has only just begun, both large and small labs are already facing some big choices over how to store the terabytes of data that these tools...

Roughly 80 percent of known protein coding genes in Saccharomyces cerevisiae are nonessential

Using chemical genomics , researchers from Stanford University and the University of Toronto demonstrated that the majority of yeast nonessential single deletions exhibit growth defects when exposed to certain chemical or environmental stress. They also identified new candidate multi-drug resistance genes and demonstrated how clustering genes based on their co-fitness can provide clues about their function. The work appeared online today in Science . “The emergent field of chemical genomics promises that, by understanding the relations between small molecules and genes on a systems level, we might understand genomic responses to small molecule perturbants,” Do you want to know more? see also