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huqionghhkk木虫 (小有名气)
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[求助]
翻译一段（药物化学）谢谢！
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For each compound we constructed a performance profile assigning binary ([0,1], binding data) or discrete (½−1;0;1 , functional data) values representing activity for a compound in a given assay, collecting such values across all assays into a vector x. Discretization of binding data are described elsewhere (48), and ChemBank data were handled similarly, except both high- and low-signal outlier values (56) were accepted (SI Datasets D6 and D7). All distinct performance profile vectors x for compounds were collected to set S, and Shannon entropy (H) was computed by calculating relative frequencies pðxÞ and summing frequency terms over x ∈ S: HðSÞ ¼ −ΣpðxÞ log2½pðxÞ (profile entropy). To calculate entropy for a set of profiles weighted by a specificity constraint, we first computed H separately for each subset S m of profiles sharing the same number m of nonzero profile features, then computed a weighted sum of these entropies with weighting factor w m ¼ exp½− lnð2Þm , to give H w ðSÞ ¼ Σw m HðS m Þ (weighted profile entropy). For ChemBank profiles, missing data were censored to zero before entropy calculations (SI Dataset D8). Statistical analyses, visualizations, and entropy calculations were performed in MATLAB. |
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爱与雨下(金币+1): ！~ 2011-08-24 08:42:52
huqionghhkk(金币+10, 翻译EPI+1): 确实不大好 谢谢 2011-08-24 13:00:18
爱与雨下(翻译EPI-1): 翻译不完全，EPI取消 2011-08-29 09:00:42
爱与雨下(金币+1): ！~ 2011-08-24 08:42:52
huqionghhkk(金币+10, 翻译EPI+1): 确实不大好 谢谢 2011-08-24 13:00:18
爱与雨下(翻译EPI-1): 翻译不完全，EPI取消 2011-08-29 09:00:42
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对于每一个化合物分子，构造了二维的模型来表现。通过测试分析得到的确定的二元数据（[0,1],边界数据）或者离散型（＆frac12；-1；0；1，函数数据）值来描述化合物的活跃度。将通过测试分析获得的所有数据收集起来得到x向量集。 边界数据的离散型在其它地方有描述（48），ChemBank数据也有相似的内容。除了高于或低于测定值（56）外都将被收集（SI数据集D6和D7）。 术语太多了，勉强翻译了一点。错误好像很多 |
2楼2011-08-23 17:25:48
