“With the help of the XSEDE allocations on supercomputers, we were able to illustrate the performance of HapSolo on genome data from three species: the Chardonnay grape, a mosquito and the thorny skate.” “Comet and Bridges were powerful enough to run our new genome sequence haplotype separation and optimization method called HapSolo,” said NSF Graduate Student Fellow Edwin Solares, first author of the journal article and also funded by the UC President’s Pre-Professoriate Fellowship. In turn, that may lead to improvements in medicine and food production for varying populations. This novel research, detailed in a January 2021 BMC Bioinformatics journal article, not only leads to improvements in genome completeness, but also helps scientists better understand the genetic relationships between individuals, populations and species. “Our work used computer science optimization methods to help resolve the accuracy of separating maternal and parental DNA in genomes.” “While sequencing genomes has become a fundamental goal and tool in science, the problem has been that many genomes have been difficult to fully resolve by sequencing because they contain distinct contributions from maternal and paternal lineages,” said Brandon Gaut, an ecology and evolutionary biology professor at UC Irvine. JUniversity of California Irvine scientists recently used National Science Foundation Extreme Science and Engineering Discovery Environment (XSEDE) allocations on Comet at the San Diego Supercomputer Center, at UC San Diego, and Bridges at the Pittsburgh Supercomputing Center, to better understand contributions from maternal and paternal lineages in genome sequences. Since 1987 - Covering the Fastest Computers in the World and the People Who Run Them
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