ArticleInfection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases2021
Alignment-free sequence comparison for virus genomes based on location correlation coefficient.
Article in Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Deciphering 6-mer Spectra Distribution Rules in Coronavirus Genomes: Application to Comparative Genomic Analysis.International journal of molecular sciences · 2026Article
- Development of a Subsequence Correlation Coefficient Feature Vector Method for High-Resolution HIV-1 Subtype Classification - China, 2004-2022.China CDC weekly · 2026Article
- CGRWDL: alignment-free phylogeny reconstruction method for viruses based on chaos game representation weighted by dynamical language model.Frontiers in microbiology · 2024Article
- SARS-CoV-2 and natural infection in animals.Journal of medical virology · 2023Review
- Proteomic Approach for Comparative Analysis of the Spike Protein of SARS-CoV-2 Omicron (B.1.1.529) Variant and Other Pango Lineages.Proteomes · 2022Article
- The complexity landscape of viral genomes.GigaScience · 2022Article
- A comprehensive genomic study, mutation screening, phylogenetic and statistical analysis of SARS-CoV-2 and its variant omicron among different countries.Journal of infection and public health · 2022Article
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5 authors.
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Abstract
Coronaviruses (especially SARS-CoV-2) are characterized by rapid mutation and wide spread. As these characteristics easily lead to global pandemics, studying the evolutionary relationship between viruses is essential for clinical diagnosis. DNA sequencing has played an important role in evolutionary analysis. Recent alignment-free methods can overcome the problems of traditional alignment-based methods, which consume both time and space. This paper proposes a novel alignment-free method called the correlation coefficient feature vector (CCFV), which defines a correlation measure of the L-step delay of a nucleotide location from its location in the original DNA sequence. The numerical feature is a 16×L-dimensional numerical vector describing the distribution characteristics of the nucleotide positions in a DNA sequence. The proposed L-step delay correlation measure is interestingly related to some types of L+1 spaced mers. Unlike traditional gene comparison, our method avoids the computational complexity of multiple sequence alignment, and hence improves the speed of sequence comparison. Our method is applied to evolutionary analysis of the common human viruses including SARS-CoV-2, Dengue virus, Hepatitis B virus, and human rhinovirus and achieves the same or even better results than alignment-based methods. Especially for SARS-CoV-2, our method also confirms that bats are potential intermediate hosts of SARS-CoV-2.
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