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Decimative Multiplication of Entropy Arrays, with Application to Influenza

机译：熵阵列的抽取乘积及其在流感中的应用

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The use of the digital signal processing procedure of decimation is introduced as a tool to detect patterns of information entropy distribution and is applied to information entropy in influenza A segment 7. Decimation was able to reveal patterns of entropy accumulation in archival and emerging segment 7 sequences that were not apparent in the complete, undecimated data. The low entropy accumulation along the first 25% of segment 7, revealed by the three frames of decimation, may be a sign of regulation at both protein and RNA levels to conserve important viral functions. Low segment 7 entropy values from the 2009 H1N1 swine flu pandemic suggests either that: (1) the viruses causing the current outbreak have convergently evolved to their low entropy state or (2) more likely, not enough time has yet passed for the entropy to accumulate. Because of its dependence upon the periodicity of the codon, the decimative procedure should be generalizable to any biological system.
机译：介绍了使用抽取的数字信号处理程序作为检测信息熵分布模式的工具，并将其应用于甲型流感7段中的信息熵。抽取能够揭示档案和新兴段7序列中的熵积累模式。在完整的，未抽取的数据中不明显。通过三个抽取框显示，沿片段7的前25％的低熵积累可能是蛋白质和RNA水平调节的信号，以保留重要的病毒功能。 2009年H1N1猪流感大流行的第7段熵值偏低表明：（1）导致当前暴发的病毒已经收敛发展到其低熵状态，或者（2）更可能的是，没有足够的时间使熵达到积累。由于它取决于密码子的周期性，因此抽取程序应可推广到任何生物系统。

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