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Search: (WFRF:(Nicholas B)) srt2:(2005-2009) > (2006)

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1.
  • Gravens, Mark B., et al. (author)
  • Physical model investigation of morphology development at headland structures
  • 2006
  • In: [Host publication title missing]. - : World Scientific Publishing Company. ; , s. 3617-3629
  • Conference paper (peer-reviewed)abstract
    • This paper describes four series of physical model experiments conducted to understand the response of the beach to headland structures. Data sets were generated for testing predictive relationships for sand transport in the presence of waves and an external current and testing of model algorithms for simulating salients and tombolos behind nearshore headland structures. The paper summarizes the experiment set up, and data collected in the physical model, processes driving the morphology development, and quantification of the time rate of morphology change behind headland structures as well as the observed sediment transport pathways.
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2.
  • Royce, Thomas E., et al. (author)
  • Extrapolating traditional DNA microarray statistics to tiling and protein microarray technologies
  • 2006
  • In: Methods in Enzymology. - 0076-6879 .- 1557-7988. ; 411, s. 282-311
  • Journal article (peer-reviewed)abstract
    • A credit to microarray technology is its broad application. Two experiments--the tiling microarray experiment and the protein microarray experiment--are exemplars of the versatility of the microarrays. With the technology's expanding list of uses, the corresponding bioinformatics must evolve in step. There currently exists a rich literature developing statistical techniques for analyzing traditional gene-centric DNA microarrays, so the first challenge in analyzing the advanced technologies is to identify which of the existing statistical protocols are relevant and where and when revised methods are needed. A second challenge is making these often very technical ideas accessible to the broader microarray community. The aim of this chapter is to present some of the most widely used statistical techniques for normalizing and scoring traditional microarray data and indicate their potential utility for analyzing the newer protein and tiling microarray experiments. In so doing, we will assume little or no prior training in statistics of the reader. Areas covered include background correction, intensity normalization, spatial normalization, and the testing of statistical significance.
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  • Result 1-2 of 2

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