22 research outputs found

    Using the information embedded in the testing sample to break the limits caused by the small sample size in microarray-based classification

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    <p>Abstract</p> <p>Background</p> <p>Microarray-based tumor classification is characterized by a very large number of features (genes) and small number of samples. In such cases, statistical techniques cannot determine which genes are correlated to each tumor type. A popular solution is the use of a subset of pre-specified genes. However, molecular variations are generally correlated to a large number of genes. A gene that is not correlated to some disease may, by combination with other genes, express itself.</p> <p>Results</p> <p>In this paper, we propose a new classiification strategy that can reduce the effect of over-fitting without the need to pre-select a small subset of genes. Our solution works by taking advantage of the information embedded in the testing samples. We note that a well-defined classification algorithm works best when the data is properly labeled. Hence, our classification algorithm will discriminate all samples best when the testing sample is assumed to belong to the correct class. We compare our solution with several well-known alternatives for tumor classification on a variety of publicly available data-sets. Our approach consistently leads to better classification results.</p> <p>Conclusion</p> <p>Studies indicate that thousands of samples may be required to extract useful statistical information from microarray data. Herein, it is shown that this problem can be circumvented by using the information embedded in the testing samples.</p

    Relative mobility determines the efficacy of MPAs in a two species mixed fishery with conflicting management objectives

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    Marine Protected Areas (MPAs) have been used to protect species in need of conservation and as a fisheries management tool. It has been suggested MPAs can benefit mobile stocks by protecting spawning grounds whilst also allowing yields to be maintained as mature fish move out of the protected areas. However, the robustness of this claim in mixed species fisheries has yet to be established. We use a simulation model to explore the efficacy of spatial closures and effort regulation when other forms of fishery control (e.g., Total Allowable Catches) are absent or non-enforced as ways of addressing management objectives that are difficult to reconcile due to the contrasting life-histories of a target and a bycatch, conservation species in a two-species fishery. The mobility of each stock in such a fishery affects the benefits conferred by an MPA. The differing management objectives of the two species can be partially met by effort regulations or closures when the species exhibit similar mobility. However, a more mobile conservation species prevents both sets of aims being met by either management tool. We use simulations to explore how spatial closures and effort regulation can be used to seek compromise between stakeholders when the mobility of one stock prevents conflicting management objectives to be fully met. Our results demonstrate that stock mobility is a key factor in considering whether an MPA can meet conflicting aims in a multispecies fishery compromised of stocks with differing life histories and mobilities

    Beyond Knox: James C. McReynolds' Other Law Clerks, 1914-1941

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    Hydrologic and water-quality characterization and modeling of the Chenoweth Run Basin, Jefferson County, Kentucky /

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    "In cooperation with the Louisville and Jefferson County Metropolitan Sewer District."Shipping list no.: 2001-0146-P.Includes bibliographical references (p. 136-139).Mode of access: Internet

    Thigh-length compression stockings and DVT after stroke

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    Controversy exists as to whether neoadjuvant chemotherapy improves survival in patients with invasive bladder cancer, despite randomised controlled trials of more than 3000 patients. We undertook a systematic review and meta-analysis to assess the effect of such treatment on survival in patients with this disease
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