ArticleBioMed research international2014
iSS-PseDNC: identifying splicing sites using pseudo dinucleotide composition.
Article in BioMed research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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62 citing papers in PubMed.
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- A Feature Fusion Predictor for RNA Pseudouridine Sites with Particle Swarm Optimizer Based Feature Selection and Ensemble Learning Approach.Current issues in molecular biology · 2021Article
- A Mini-review of the Computational Methods Used in Identifying RNA 5-Methylcytosine Sites.Current genomics · 2020Review
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- iProEP: A Computational Predictor for Predicting Promoter.Molecular therapy. Nucleic acids · 2019Article
- An advanced approach to identify antimicrobial peptides and their function types for penaeus through machine learning strategies.BMC bioinformatics · 2019Article
- Recognition of 3'-end L1, Alu, processed pseudogenes, and mRNA stem-loops in the human genome using sequence-based and structure-based machine-learning models.Scientific reports · 2019Article
- HseSUMO: Sumoylation site prediction using half-sphere exposures of amino acids residues.BMC genomics · 2019Article
- A high-performance approach for predicting donor splice sites based on short window size and imbalanced large samples.Biology direct · 2019Article
- HRGPred: Prediction of herbicide resistant genes with k-mer nucleotide compositional features and support vector machine.Scientific reports · 2019Article
- Identification of D Modification Sites by Integrating Heterogeneous Features inMolecules (Basel, Switzerland) · 2019Article
- Identification of Phage Viral Proteins With Hybrid Sequence Features.Frontiers in microbiology · 2019Article
- Structural Variability in the RLR-MAVS Pathway and Sensitive Detection of Viral RNAs.Medicinal chemistry (Shariqah (United Arab Emirates)) · 2019Review
- SFPEL-LPI: Sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions.PLoS computational biology · 2018Article
- Predicting membrane proteins and their types by extracting various sequence features into Chou's general PseAAC.Molecular biology reports · 2018Article
- A Comprehensive In Silico Method to Study the QSTR of the Aconitine Alkaloids for Designing Novel Drugs.Molecules (Basel, Switzerland) · 2018Article
- Identifying Phage Virion Proteins by Using Two-Step Feature Selection Methods.Molecules (Basel, Switzerland) · 2018Article
- SeqSVM: A Sequence-Based Support Vector Machine Method for Identifying Antioxidant Proteins.International journal of molecular sciences · 2018Article
2 more citing papers are in PubMed but not listed here.
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4 authors.
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Abstract
In eukaryotic genes, exons are generally interrupted by introns. Accurately removing introns and joining exons together are essential processes in eukaryotic gene expression. With the avalanche of genome sequences generated in the postgenomic age, it is highly desired to develop automated methods for rapid and effective detection of splice sites that play important roles in gene structure annotation and even in RNA splicing. Although a series of computational methods were proposed for splice site identification, most of them neglected the intrinsic local structural properties. In the present study, a predictor called "iSS-PseDNC" was developed for identifying splice sites. In the new predictor, the sequences were formulated by a novel feature-vector called "pseudo dinucleotide composition" (PseDNC) into which six DNA local structural properties were incorporated. It was observed by the rigorous cross-validation tests on two benchmark datasets that the overall success rates achieved by iSS-PseDNC in identifying splice donor site and splice acceptor site were 85.45% and 87.73%, respectively. It is anticipated that iSS-PseDNC may become a useful tool for identifying splice sites and that the six DNA local structural properties described in this paper may provide novel insights for in-depth investigations into the mechanism of RNA splicing.
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