ArticlePloS one2014
Prediction of aptamer-target interacting pairs with pseudo-amino acid composition.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 59 citations in OpenAlex.
- Evolutionary Dynamics-AwareACS omega · 2026Article
- Interpretable prediction and generation of ASC-speck aptamers using multiscale deep biological learning models.Bioinformatics advances · 2026Article
- Designing the Future of Biosensing: Advances in Aptamer Discovery, Computational Modeling, and Diagnostic Applications.Biosensors · 2025Review
- AI-Enhanced Electrochemical Sensing Systems: A Paradigm Shift for Intelligent Food Safety Monitoring.Biosensors · 2025Review
- DeepAptamer: Advancing high-affinity aptamer discovery with a hybrid deep learning model.Molecular therapy. Nucleic acids · 2025Article
- Innovative Applications of Nucleic Acid Aptamers in Colorectal Cancer Diagnosis and Therapy: From Selection Optimization to Clinical Translation.International journal of nanomedicine · 2025Review
- APIPred: An XGBoost-Based Method for Predicting Aptamer-Protein Interactions.Journal of chemical information and modeling · 2024Article
- AptaTrans: a deep neural network for predicting aptamer-protein interaction using pretrained encoders.BMC bioinformatics · 2023Article
- DAPTEV: Deep aptamer evolutionary modelling for COVID-19 drug design.PLoS computational biology · 2023Article
- Design and Prediction of Aptamers Assisted by In Silico Methods.Biomedicines · 2023Review
- Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines?Nano today · 2022Article
- Article
- In silico design of novel aptamers utilizing a hybrid method of machine learning and genetic algorithm.Molecular diversity · 2021Review
- A novel artificial intelligence-based approach for identification of deoxynucleotide aptamers.PLoS computational biology · 2021Article
- Anti-Proliferative Effect of Doxorubicin-Loaded AS1411 Aptamer on Colorectal Cancer Cell.Asian Pacific journal of cancer prevention : APJCP · 2021Article
- Using an Ensemble to Identify and Classify Macroalgae Antimicrobial Peptides.Interdisciplinary sciences, computational life sciences · 2021Article
- Artificial Intelligence in Aptamer-Target Binding Prediction.International journal of molecular sciences · 2021Review
- AptaNet as a deep learning approach for aptamer-protein interaction prediction.Scientific reports · 2021Article
- Article
- PPAI: a web server for predicting protein-aptamer interactions.BMC bioinformatics · 2020Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aptamers are oligonucleic acid or peptide molecules that bind to specific target molecules. As a novel and powerful class of ligands, aptamers are thought to have excellent potential for applications in the fields of biosensing, diagnostics and therapeutics. In this study, a new method for predicting aptamer-target interacting pairs was proposed by integrating features derived from both aptamers and their targets. Features of nucleotide composition and traditional amino acid composition as well as pseudo amino acid were utilized to represent aptamers and targets, respectively. The predictor was constructed based on Random Forest and the optimal features were selected by using the maximum relevance minimum redundancy (mRMR) method and the incremental feature selection (IFS) method. As a result, 81.34% accuracy and 0.4612 MCC were obtained for the training dataset, and 77.41% accuracy and 0.3717 MCC were achieved for the testing dataset. An optimal feature set of 220 features were selected, which were considered as the ones that contributed significantly to the interacting aptamer-target pair predictions. Analysis of the optimal feature set indicated several important factors in determining aptamer-target interactions. It is anticipated that our prediction method may become a useful tool for identifying aptamer-target pairs and the features selected and analyzed in this study may provide useful insights into the mechanism of interactions between aptamers and targets.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.