AI Article Synopsis
- The study introduces a new method for visualizing genomic data by analyzing coding sequences as sets of non-stop codons, which creates a partition of codons.
- The concept of mixing character is explored, mathematically linked to a property called majorization, enhancing the understanding of how partitions are organized.
- A theoretical mixing space (TGMS) is developed from over a million partitions, and a genome mixing signature (GMS) is created, with examples from 19 different species, including humans, provided for discussion.
Article Abstract
We report on a novel way to visualize genomic data. By considering genome coding sequences, cds, as sets of the N=61 non-stop codons, one obtains a partition of the total number of codons in each cds. Partitions exhibit a statistical property known as mixing character which characterizes how mixed the partition is. Mixing characters have been shown mathematically to exhibit a partial order known as majorization (Ruch, 1975). In previous work (Seitz and Kirwan, 2022) we developed an approach that combined mixing and entropy that is visualized as a scatter plot. If we consider all 1,121,505 partitions of 61 codons, this produces a plot we call the theoretical mixing space, TGMS. A normalization procedure is developed here and applied to real genomic data to produce the genome mixing signature, GMS. Example GMS's of 19 species, including Homo sapiens, are shown and discussed.
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| http://dx.doi.org/10.1016/j.biosystems.2023.104839 | DOI Listing |
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