Author: Karthi Balasubramanian; Nithin Nagaraj
Title: Automatic Identification of SARS Coronavirus using Compression-Complexity Measures Document date: 2020_3_27
ID: ljli6a2z_29
Snippet: Our primary interest in this work lies in showing that it is not necessary to have the entire genome/gene for complexity analysis. In this work, we use LZ and Effort-To-Compress (ETC) [37] complexity measures to analyze short length segments that are randomly chosen from genome sequences. In particular, short length contiguous segments (length < 100) are randomly chosen from the sequence for analysis......
Document: Our primary interest in this work lies in showing that it is not necessary to have the entire genome/gene for complexity analysis. In this work, we use LZ and Effort-To-Compress (ETC) [37] complexity measures to analyze short length segments that are randomly chosen from genome sequences. In particular, short length contiguous segments (length < 100) are randomly chosen from the sequence for analysis.
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