ArticleScientific reports2017
Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix.
Article in Scientific reports, 2017. 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 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Genome Wide Identification and Characterization of LIM Domain Associated Gene Superfamily in Common Bean (International journal of genomics · 2025Article
- Bioinformatics analysis and alternative polyadenylation in Heat Shock Proteins 70 (HSP70) family members.International journal of physiology, pathophysiology and pharmacology · 2024Article
- Review
- Albertson (Frontiers in chemistry · 2023Article
- Mathematical Approach to Protein Sequence Comparison Based on Physiochemical Properties.ACS omega · 2022Article
- An accurate alignment-free protein sequence comparator based on physicochemical properties of amino acids.Scientific reports · 2022Article
- FEGS: a novel feature extraction model for protein sequences and its applications.BMC bioinformatics · 2021Article
- PredCRG: A computational method for recognition of plant circadian genes by employing support vector machine with Laplace kernel.Plant methods · 2021Article
- Protein-Protein Interactions Prediction Based on Graph Energy and Protein Sequence Information.Molecules (Basel, Switzerland) · 2020Article
- Prediction of Protein-Protein Interactions with Local Weight-Sharing Mechanism in Deep Learning.BioMed research international · 2020Article
- RF-MaloSite and DL-Malosite: Methods based on random forest and deep learning to identify malonylation sites.Computational and structural biotechnology journal · 2020Article
- FCTP-WSRC: Protein-Protein Interactions PredictionFrontiers in genetics · 2020Article
- DCGR: feature extractions from protein sequences based on CGR via remodeling multiple information.BMC bioinformatics · 2019Article
- Alignment-free similarity analysis for protein sequences based on fuzzy integral.Scientific reports · 2019Article
- A novel model for protein sequence similarity analysis based on spectral radius.Journal of theoretical biology · 2018Article
- Protein Sequence Comparison and DNA-binding Protein Identification with Generalized PseAAC and Graphical Representation.Combinatorial chemistry & high throughput screening · 2018Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We develop a novel position-feature-based model for protein sequences by employing physicochemical properties of 20 amino acids and the measure of graph energy. The method puts the emphasis on sequence order information and describes local dynamic distributions of sequences, from which one can get a characteristic B-vector. Afterwards, we apply the relative entropy to the sequences representing B-vectors to measure their similarity/dissimilarity. The numerical results obtained in this study show that the proposed methods leads to meaningful results compared with competitors such as Clustal W.
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Registered trials
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