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帮忙翻译一段生物物种系统分析的文献
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Three different metrics were used to characterize intra-specific divergence: (i) average pairwise distances between all individuals sampled within those species that had at least two representatives, (ii) ‘mean theta’, with theta being the average pairwise distances calculated for each species that had more than one representative, thereby eliminating biases associated with uneven sampling among taxa and (iii) average coalescent depth, i.e. the depth of a node linking all sampled extant members of a species, ‘book-ending’ intra-specific variability. Genetic distances between con-generic species were used to characterize inter-specific divergence. For each barcode, pairwise distances were calculated with the simplest K2P model following Lahaye et al. 20 in which this model showed the best results. This model also utilizes the CBOL advises for distance calculations (barcoding.si.edu/). Wilcoxon Signed Rank Tests were performed to compare intra- and inter-specific variability for every pair of barcodes following Kress and Erickson 24. We evaluated ‘DNA barcoding gaps’ 23 by comparing the distribution of intra- versus inter-specific divergences. Median and Wilcoxon Two-Sample Tests were used to evaluate whether these distributions overlapped. 原文见： http://precedings.nature.com/doc ... /npre20081896-1.pdf （第9页开始部分） [ Last edited by wmwman306 on 2009-4-10 at 10:49 ] |
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fisherman1051
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wmwman306(金币+5,VIP+0):谢谢！还是不行，呵呵 4-10 13:35
wmwman306(金币+5,VIP+0):谢谢！还是不行，呵呵 4-10 13:35
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我也学生物的，试试看能不能帮忙哈。 使用三个尺度来表征种间的差异性。（i）所有至少具有两个样本的物种的独立样本之间的平均配对距离；（ii）平均系数，计算超过一个样本的物种的平均配对距离的系数，由此减少在分类群中与奇数样本相关的偏差和（iii）平均联合深度，也就是将每个作为样本的物种现存的成员连接到一起的结点深度，“book-ending”不好理解，暂时翻译为用书面的方式去掉种类差异。同源物种之间的遗传距离用来表征种间差异。对于每个编码而言，配对距离按照Lahaye等20的最简K2P模型进行计算出此模型中表现最好的样本。同时这个模型利用CBOL表示出了距离。（编码.si.edu/）根据Kress和Erickson24采用的Wilcoxon符号秩检验比较每对编码的种内和种间差异。DNA编码缺失23的估值通过比较种内和种间的差异分布进行。利用中位数和Wilcoxon双样本检验评定分布是否重复。 红色的是不太确定的，你自己联系上下文修改，我不想看你的原文。内容里提到的数字应该是引用文献的编号哈。 大概翻成这样，希望对你有用。 [ Last edited by fisherman1051 on 2009-4-10 at 12:17 ] |
2楼2009-04-10 11:23:48
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