  A comprehensive overview of the recent physics-inspired genome analysis tool,
GenomeBits, is presented. This is based on traditional signal processing
methods such as Discrete Fourier Transform (DFT). GenomeBits can be used to
extract underlying genomics features from the distribution of nucleotides, and
can be further used to analyze the mutation patterns in viral genomes. Examples
of the main GenomeBits findings outlining the intrinsic signal organization of
genomics sequences for different SARS-CoV-2 variants along the pandemic years
2020-2022 and Monkeypox cases in 2021 are presented to show the usefulness of
GenomeBits. GenomeBits results for DFT of SARS-CoV-2 genomes in different
geographical regions are discussed together with the GenomeBits analysis of
complete genome sequences for the first coronavirus variants reported: Alpha,
Beta, Gamma, Epsilon and Eta. Interesting features of the Delta and Omicron
variants in the form of a unique "order-disorder" transition are uncovered from
these samples as well as from their cumulative distribution function and
scatter plots. This class of transitions might reveal the cumulative outcome of
mutations on the spike protein. A salient feature of GenomeBits is the mapping
of the nucleotide bases (A,T,C,G) into an alternating spin-like numerical
sequence via a series having binary (0,1) indicators for each A,T,C,G. This
leads to derive a set of statistical distribution curves. Furthermore, the
quantum-based extension of the GenomeBits model to an analogous probability
measure is shown to identify properties of genome sequences as wavefunctions
via a superposition of states. An association of the integral of the GenomeBits
coding and a binding-like energy can in principle also be established. The
relevance of these different results in Bioinformatics is analyzed.
