ArticlePloS one2011
A novel method of characterizing genetic sequences: genome space with biological distance and applications.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 50 papers.
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Who cites it
50 citing papers in PubMed.
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- Energy entropy vector: a novel approach for efficient microbial genomic sequence analysis and classification.Briefings in bioinformatics · 2025Article
- The grand biological universe: A comprehensive geometric construction of genome space.Innovation (Cambridge (Mass.)) · 2025Article
- Reconstruction of masked sequencesPeerJ · 2025Article
- The optimal metric for viral genome space.Computational and structural biotechnology journal · 2024Article
- Levy Sooty Tern Optimization Algorithm Builds DNA Storage Coding Sets for Random Access.Entropy (Basel, Switzerland) · 2024Article
- Exploring geometry of genome space via Grassmann manifolds.Innovation (Cambridge (Mass.)) · 2024Article
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- Investigating alignment-free machine learning methods for HIV-1 subtype classification.Bioinformatics advances · 2024Article
- Automated recognition of chromosome fusion using an alignment-free natural vector method.Frontiers in genetics · 2024Article
- Generating Minimal Models of H1N1 NS1 Gene Sequences Using Alignment-Based and Alignment-Free Algorithms.Genes · 2023Article
- Deep-STP: a deep learning-based approach to predict snake toxin proteins by using word embeddings.Frontiers in medicine · 2023Article
- Empirical comparison and recent advances of computational prediction of hormone binding proteins using machine learning methods.Computational and structural biotechnology journal · 2023Review
- Protein-protein interaction and non-interaction predictions using gene sequence natural vector.Communications biology · 2022Article
- An efficient numerical representation of genome sequence: natural vector with covariance component.PeerJ · 2022Article
- In-depth investigation of the point mutation pattern of HIV-1.Frontiers in cellular and infection microbiology · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
Abstract
backgroundMost existing methods for phylogenetic analysis involve developing an evolutionary model and then using some type of computational algorithm to perform multiple sequence alignment. There are two problems with this approach: (1) different evolutionary models can lead to different results, and (2) the computation time required for multiple alignments makes it impossible to analyse the phylogeny of a whole genome. This motivates us to create a new approach to characterize genetic sequences. METHODOLOGY: To each DNA sequence, we associate a natural vector based on the distributions of nucleotides. This produces a one-to-one correspondence between the DNA sequence and its natural vector. We define the distance between two DNA sequences to be the distance between their associated natural vectors. This creates a genome space with a biological distance which makes global comparison of genomes with same topology possible. We use our proposed method to analyze the genomes of the new influenza A (H1N1) virus, human rhinoviruses (HRV) and mammalian mitochondrial. The result shows that a triple-reassortant swine virus circulating in North America and the Eurasian swine virus belong to the lineage of the influenza A (H1N1) virus. For the HRV and mammalian mitochondrial genomes, the results coincide with biologists' analyses.
conclusionsOur approach provides a powerful new tool for analyzing and annotating genomes and their phylogenetic relationships. Whole or partial genomes can be handled more easily and more quickly than using multiple alignment methods. Once a genome space has been constructed, it can be stored in a database. There is no need to reconstruct the genome space for subsequent applications, whereas in multiple alignment methods, realignment is needed to add new sequences. Furthermore, one can make a global comparison of all genomes simultaneously, which no other existing method can achieve.
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