ArticlePeerJ2022
An efficient numerical representation of genome sequence: natural vector with covariance component.
Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Energy entropy vector: a novel approach for efficient microbial genomic sequence analysis and classification.Briefings in bioinformatics · 2025Article
- Overview and Prospects of DNA Sequence Visualization.International journal of molecular sciences · 2025Review
- MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data.Briefings in bioinformatics · 2024Article
- Investigating alignment-free machine learning methods for HIV-1 subtype classification.Bioinformatics advances · 2024Article
- In-depth investigation of the point mutation pattern of HIV-1.Frontiers in cellular and infection microbiology · 2022Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: The characterization and comparison of microbial sequences, including archaea, bacteria, viruses and fungi, are very important to understand their evolutionary origin and the population relationship. Most methods are limited by the sequence length and lack of generality. The purpose of this study is to propose a general characterization method, and to study the classification and phylogeny of the existing datasets. Methods: We present a new alignment-free method to represent and compare biological sequences. By adding the covariance between each two nucleotides, the new 18-dimensional natural vector successfully describes 24,250 genomic sequences and 95,542 DNA barcode sequences. The new numerical representation is used to study the classification and phylogenetic relationship of microbial sequences. Results: First, the classification results validate that the six-dimensional covariance vector is necessary to characterize sequences. Then, the 18-dimensional natural vector is further used to conduct the similarity relationship between giant virus and archaea, bacteria, other viruses. The nearest distance calculation results reflect that the giant viruses are closer to bacteria in distribution of four nucleotides. The phylogenetic relationships of the three representative families, Mimiviridae, Pandoraviridae and Marsellieviridae from giant viruses are analyzed. The trees show that ten sequences of Mimiviridae are clustered with Pandoraviridae, and Mimiviridae is closer to the root of the tree than Marsellieviridae. The new developed alignment-free method can be computed very fast, which provides an effective numerical representation for the sequence of microorganisms.
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