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Search: WFRF:(Ruttenberg Alan)

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1.
  • Deans, Andrew R, et al. (author)
  • Finding Our Way through Phenotypes.
  • 2015
  • In: PLoS Biology. - : Public Library of Science (PLoS). - 1545-7885. ; 13:1
  • Journal article (peer-reviewed)abstract
    • Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.
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2.
  • Ho, Ching-Tien, et al. (author)
  • Systolic FFT Algorithms on Boolean Cubes
  • 1988
  • Conference paper (peer-reviewed)abstract
    • A description is given of a systolic Cooley-Tukey fast Fourier transform algorithm for Booleann-cubes with a substantial amount of storage per cube node. In mapping a Cooley-Tukey type FFT to such a network, the main concerns are effective use of the high connectivity/bandwidth of the Booleann-cube, the computational resources, the storage bandwidth, if there is a storage hierarchy, and the pipelines should the arithmetic units have such a feature. Another important consideration in a multiprocessor, distributed storage architecture is the allocation and access to coefficients, if they are precomputed. FFT algorithms are described that use both the storage bandwidth and the communication system optimally and require storage ofP+nNcoefficients for a transform onP⩾Ndata elements. A complex-to-complex FFT on 16 million points is predicted to require about 1.5 s on a Connection Machine model CM-2
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