ArticleBMC bioinformatics2019
Integrated entropy-based approach for analyzing exons and introns in DNA sequences.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- DNA Sequence Perplexity Reveals Evolutionarily Conserved Patterns in cis-Regulatory Regions Across Diverse Species.Biochemical genetics · 2026Article
- GBRAP: A Comprehensive Database and Tool for Exploring Genomic Diversity Across All Domains of Life.Molecular biology and evolution · 2025Article
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- IIMLP: integrated information-entropy-based method for LncRNA prediction.BMC bioinformatics · 2021Article
- Spatial constrains and information content of sub-genomic regions of the human genome.iScience · 2021Article
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10 authors.
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Abstract
backgroundNumerous essential algorithms and methods, including entropy-based quantitative methods, have been developed to analyze complex DNA sequences since the last decade. Exons and introns are the most notable components of DNA and their identification and prediction are always the focus of state-of-the-art research.
resultsIn this study, we designed an integrated entropy-based analysis approach, which involves modified topological entropy calculation, genomic signal processing (GSP) method and singular value decomposition (SVD), to investigate exons and introns in DNA sequences. We optimized and implemented the topological entropy and the generalized topological entropy to calculate the complexity of DNA sequences, highlighting the characteristics of repetition sequences. By comparing digitalizing entropy values of exons and introns, we observed that they are significantly different. After we converted DNA data to numerical topological entropy value, we applied SVD method to effectively investigate exon and intron regions on a single gene sequence. Additionally, several genes across five species are used for exon predictions.
conclusionsOur approach not only helps to explore the complexity of DNA sequence and its functional elements, but also provides an entropy-based GSP method to analyze exon and intron regions. Our work is feasible across different species and extendable to analyze other components in both coding and noncoding region of DNA sequences.
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