ArticleRNA (New York, N.Y.)2010
Computational approaches toward the design of pools for the in vitro selection of complex aptamers.
Article in RNA (New York, N.Y.), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Fluorescence Anisotropy Applied to Measure Aptamer-Protein Interactions.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Targeting cobra venom cytotoxin: a linear 40-mer ssDNA aptamer-based antivenom confers neutralisation potentials against cobra venom-induced cytotoxicity.Archives of toxicology · 2026Article
- Review
- Selection of DNA aptamers that prevent the fibrillization of α-synuclein protein in cellular and mouse models.Molecular therapy. Nucleic acids · 2024Article
- Minimizing amplification bias during reverse transcription for in vitro selections.RNA (New York, N.Y.) · 2023Article
- In vitro selection of aptamers and their applications.Nature reviews. Methods primers · 2023Article
- SELEX: Critical factors and optimization strategies for successful aptamer selection.Biotechnology and applied biochemistry · 2022Review
- Electrochemical Aptasensors for Antibiotics Detection: Recent Achievements and Applications for Monitoring Food Safety.Sensors (Basel, Switzerland) · 2022Review
- Methods and Applications of In Silico Aptamer Design and Modeling.International journal of molecular sciences · 2020Review
- Developments of Riboswitches and Toehold Switches for Molecular Detection-Biosensing and Molecular Diagnostics.International journal of molecular sciences · 2020Review
- Selection and application of aptamers with high-affinity and high-specificity against dinophysistoxin-1.RSC advances · 2020Article
- Inside the Black Box: What Makes SELEX Better?Molecules (Basel, Switzerland) · 2019Review
- A Bottom-Up Approach for Developing Aptasensors for Abused Drugs: Biosensors in Forensics.Biosensors · 2019Review
- Article
- Molecular Modeling Applied to Nucleic Acid-Based Molecule Development.Biomolecules · 2018Review
- Key Aspects of Nucleic Acid Library Design for in Vitro Selection.International journal of molecular sciences · 2018Review
- Favorable biodistribution, specific targeting and conditional endosomal escape of RNA nanoparticles in cancer therapy.Cancer letters · 2018Review
- Controlling uncertainty in aptamer selection.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Opportunities in the design and application of RNA for gene expression control.Nucleic acids research · 2016Review
- In silico selection of an aptamer to estrogen receptor alpha using computational docking employing estrogen response elements as aptamer-alike molecules.Scientific reports · 2016Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is well known that using random RNA/DNA sequences for SELEX experiments will generally yield low-complexity structures. Early experimental results suggest that having a structurally diverse library, which, for instance, includes high-order junctions, may prove useful in finding new functional motifs. Here, we develop two computational methods to generate sequences that exhibit higher structural complexity and can be used to increase the overall structural diversity of initial pools for in vitro selection experiments. Random Filtering selectively increases the number of five-way junctions in RNA/DNA pools, and Genetic Filtering designs RNA/DNA pools to a specified structure distribution, whether uniform or otherwise. We show that using our computationally designed DNA pool greatly improves access to highly complex sequence structures for SELEX experiments (without losing our ability to select for common one-way and two-way junction sequences).
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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.