ArticleScientific reports2019
Alignment-free similarity analysis for protein sequences based on fuzzy integral.
Article in Scientific reports, 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.
- 20D-Dynamic Representation of Protein Sequences Combined with K-means Clustering.Combinatorial chemistry & high throughput screening · 2026Article
- Identification and Optimization of more Efficient Olivetolic Acid Synthases.Cannabis and cannabinoid research · 2024Article
- Article
- FFP: joint Fast Fourier transform and fractal dimension in amino acid property-aware phylogenetic analysis.BMC bioinformatics · 2022Article
- An accurate alignment-free protein sequence comparator based on physicochemical properties of amino acids.Scientific reports · 2022Article
- A new graph-theoretic approach to determine the similarity of genome sequences based on nucleotide triplets.Genomics · 2020Article
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3 authors.
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Abstract
Sequence comparison is an essential part of modern molecular biology research. In this study, we estimated the parameters of Markov chain by considering the frequencies of occurrence of the all possible amino acid pairs from each alignment-free protein sequence. These estimated Markov chain parameters were used to calculate similarity between two protein sequences based on a fuzzy integral algorithm. For validation, our result was compared with both alignment-based (ClustalW) and alignment-free methods on six benchmark datasets. The results indicate that our developed algorithm has a better clustering performance for protein sequence comparison.
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