decimative multiplication of entropy arrays, with application to influenzadecimative乘法熵的阵列,应用流感.pdf

Entropy 2009, 11, 351-359; doi:10.3390/ OPEN ACCESS entropy ISSN 1099-4300 /journal/entropy Article Decimative Multiplication of Entropy Arrays, with Application to Influenza William A. Thompson 1, Andy Martwick 2 and Joel K. Weltman 3,* 1 Division of Applied Mathematics and Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA; E-mail: william_thompson_1@ 2 Department of Physics, Portland State University, Portland, OR 97207, USA; E-mail: martwick@ 3 Department of Medicine, Alpert Medical School of Brown University, Providence, RI 02912, USA * Author to whom correspondence should be addressed; E-mail: joel_weltman@ Received: 17 May 2009 / Accepted: 29 July 2009 / Published: 31 July 2009 Abstract: 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 entrop