ArticleRNA (New York, N.Y.)2007
A computational proposal for designing structured RNA pools for in vitro selection of RNAs.
Article in RNA (New York, N.Y.), 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Minimizing amplification bias during reverse transcription for in vitro selections.RNA (New York, N.Y.) · 2023Article
- Secondary Structure Libraries for Artificial Evolution Experiments.Molecules (Basel, Switzerland) · 2021Article
- Methods and Applications of In Silico Aptamer Design and Modeling.International journal of molecular sciences · 2020Review
- Identification of novel RNA design candidates by clustering the extended RNA-As-Graphs library.Biochimica et biophysica acta. General subjects · 2020Article
- Inside the Black Box: What Makes SELEX Better?Molecules (Basel, Switzerland) · 2019Review
- Article
- A pipeline for computational design of novel RNA-like topologies.Nucleic acids research · 2018Article
- Adventures with RNA graphs.Methods (San Diego, Calif.) · 2018Review
- Key Aspects of Nucleic Acid Library Design for in Vitro Selection.International journal of molecular sciences · 2018Review
- F-RAG: Generating Atomic Coordinates from RNA Graphs by Fragment Assembly.Journal of molecular biology · 2017Article
- Predicting Large RNA-Like Topologies by a Knowledge-Based Clustering Approach.Journal of molecular biology · 2016Article
- Aptamers as both drugs and drug-carriers.BioMed research international · 2014Review
- RNA graph partitioning for the discovery of RNA modularity: a novel application of graph partition algorithm to biology.PloS one · 2014Article
- Network Theory Tools for RNA Modeling.WSEAS transactions on mathematics · 2013Article
- Article
- Dynamic energy landscapes of riboswitches help interpret conformational rearrangements and function.PLoS computational biology · 2012Article
- Computational approaches to RNA structure prediction, analysis, and design.Current opinion in structural biology · 2011Review
- RAG: an update to the RNA-As-Graphs resource.BMC bioinformatics · 2011Article
- Computational approaches toward the design of pools for the in vitro selection of complex aptamers.RNA (New York, N.Y.) · 2010Article
- Nucleotides that are essential but not conserved; a sufficient L-tryptophan site in RNA.RNA (New York, N.Y.) · 2010Article
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Authors and funding
3 authors.
Funding
Abstract
Although in vitro selection technology is a versatile experimental tool for discovering novel synthetic RNA molecules, finding complex RNA molecules is difficult because most RNAs identified from random sequence pools are simple motifs, consistent with recent computational analysis of such sequence pools. Thus, enriching in vitro selection pools with complex structures could increase the probability of discovering novel RNAs. Here we develop an approach for engineering sequence pools that links RNA sequence space regions with corresponding structural distributions via a "mixing matrix" approach combined with a graph theory analysis. We define five classes of mixing matrices motivated by covariance mutations in RNA; these constructs define nucleotide transition rates and are applied to chosen starting sequences to yield specific nonrandom pools. We examine the coverage of sequence space as a function of the mixing matrix and starting sequence via clustering analysis. We show that, in contrast to random sequences, which are associated only with a local region of sequence space, our designed pools, including a structured pool for GTP aptamers, can target specific motifs. It follows that experimental synthesis of designed pools can benefit from using optimized starting sequences, mixing matrices, and pool fractions associated with each of our constructed pools as a guide. Automation of our approach could provide practical tools for pool design applications for in vitro selection of RNAs and related problems.
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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.