Selected article for: "LZ complexity measure and relative distance"
Author: Karthi Balasubramanian; Nithin Nagaraj
Title: Automatic Identification of SARS Coronavirus using Compression-Complexity Measures
  • Document date: 2020_3_27
    • ID: ljli6a2z_40
    Snippet: We propose a very simple criteria for identification of sequences by proposing a distance measure which is computed using a compression-complexity measure (LZ or ETC). Let us say that we have genome sequences of three viruses V 1 , V 2 and V 3 . Firstly, we form new sequences V 1 V 2 and V 2 V 1 by concatenation 5 . We then compute the complexity measures ET C(V 1 ), ET C(V 2 ), ET C(V 1 V 2 ) and ET C(V 2 V 1 ) (similarly for LZ). In line with w.....
    Document: We propose a very simple criteria for identification of sequences by proposing a distance measure which is computed using a compression-complexity measure (LZ or ETC). Let us say that we have genome sequences of three viruses V 1 , V 2 and V 3 . Firstly, we form new sequences V 1 V 2 and V 2 V 1 by concatenation 5 . We then compute the complexity measures ET C(V 1 ), ET C(V 2 ), ET C(V 1 V 2 ) and ET C(V 2 V 1 ) (similarly for LZ). In line with what has been used by Otu et al. [15] in Equation 4, we propose a distance measure given by the average of the relative distances between the complexity values of the two concatenated sequences V 1 V 2 and V 2 V 1 . Mathematically, they are described as:

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