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信息论拓宽了分子生态学和进化的研究范围。

Information Theory Broadens the Spectrum of Molecular Ecology and Evolution.

机构信息

Evolution and Ecology Research Centre, School of Biological Earth and Environmental Science, University of New South Wales, Sydney, NSW 2052, Australia; Murdoch University Cetacean Research Unit, Murdoch University, South Road, Murdoch, WA 6150, Australia.

Institute of Statistics, National Tsing Hua University, Hsin-Chu 30043, Taiwan.

出版信息

Trends Ecol Evol. 2017 Dec;32(12):948-963. doi: 10.1016/j.tree.2017.09.012. Epub 2017 Nov 7.

Abstract

Information or entropy analysis of diversity is used extensively in community ecology, and has recently been exploited for prediction and analysis in molecular ecology and evolution. Information measures belong to a spectrum (or q profile) of measures whose contrasting properties provide a rich summary of diversity, including allelic richness (q=0), Shannon information (q=1), and heterozygosity (q=2). We present the merits of information measures for describing and forecasting molecular variation within and among groups, comparing forecasts with data, and evaluating underlying processes such as dispersal. Importantly, information measures directly link causal processes and divergence outcomes, have straightforward relationship to allele frequency differences (including monotonicity that q=2 lacks), and show additivity across hierarchical layers such as ecology, behaviour, cellular processes, and nongenetic inheritance.

摘要

多样性的信息或熵分析在群落生态学中得到了广泛的应用,最近在分子生态学和进化中也被用于预测和分析。信息度量属于一个度量(或 q 分布)的谱,其对比特性为多样性提供了丰富的总结,包括等位基因丰富度(q=0)、香农信息(q=1)和杂合度(q=2)。我们介绍了信息度量在描述和预测群体内和群体间分子变异方面的优点,将预测与数据进行了比较,并评估了扩散等潜在过程。重要的是,信息度量直接将因果过程和分歧结果联系起来,与等位基因频率差异有直接关系(包括 q=2 缺乏的单调性),并且在生态学、行为、细胞过程和非遗传遗传等层次结构上具有可加性。

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