遗传资源数据分析的图论新技术

R.L. Burt, W.T. Williams, D.J. Abel
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引用次数: 7

摘要

综述了遗传资源数据分析的问题,特别提到图论方法的使用和“验证”的概念。对一组分类困难的柱花草(豆科)资料进行了分类、最小生成树和双邻居网络。然后,它将受到一种新的多近邻方法(程序NEBALL)的影响,该方法提供了更详细和准确的配置摘要;这是通过对植物化学、种源和性能数据的呼吁来验证的。结果表明,如果模型中隐含的假设得到满足,新技术很可能是遗传资源数据研究中最强大的技术。
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A new graph-theoretic technique for the analysis of genetic resources data

The problems of analysing genetic resources data are reviewed, with particular reference to the use of graph-theoretic methods and to the concept of “validation”. A taxonomically difficult set of Stylosanthes (Leguminosae) accessions is subjected to classification, a minimum spanning tree, and a two-neighbour network. It is then subjected to a novel multiple-nearest-neighbour approach (program NEBALL) which provides a more detailed and exact summary of the configuration; this is validated by appeal to phytochemical, provenance and performance data. The results suggest that, providing the assumptions implicit in the model are met, the new technique may well be the most powerful yet available for the study of genetic resources data.

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