1,721,108 research outputs found
A BLAS-based algorithm for finding position weight matrix occurrences in DNA sequences on CPUs and GPUs
BLAMM: BLAS-based algorithm for finding position weight matrix occurrences in DNA sequences on CPUs and GPUs
A GRID computer implementation of the multilevel fast multipole algorithm for full-wave analysis of optical devices
Oracle selection provides insight into how far off practice is from Utopia in plant breeding
Since the introduction of genomic selection in plant breeding, high genetic gains have been realized in different plant breeding programs. Various methods based on genomic estimated breeding values (GEBVs) for selecting parental lines that maximize the genetic gain as well as methods for improving the predictive performance of genomic selection have been proposed. Unfortunately, it remains difficult to measure to what extent these methods really maximize long-term genetic values. In this study, we propose oracle selection, a hypothetical frame of mind that uses the ground truth to optimally select parents or optimize the training population in order to maximize the genetic gain in each breeding cycle. Clearly, oracle selection cannot be applied in a true breeding program, but allows for the assessment of existing parental selection and training population update methods and the evaluation of how far these methods are from the optimal utopian solution
Adaptive scoping: balancing short- and long-term genetic gain in plant breeding
Funding was provided by Ghent University
Illumina error correction near highly repetitive DNA regions improves de novo genome assembly
Fast and accurate evaluation of enclosures with the Method of Moments by using splay trees
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