ArticleNature biotechnology2005
Design of a genome-wide siRNA library using an artificial neural network.
Article in Nature biotechnology, 2005. 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 160 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.
The trial behind it
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
160 citing papers in PubMed, 377 citations in OpenAlex.
- From RNA design to delivery: Computational strategies for functional RNA therapeutics.Bioactive materials · 2027Review
- From rules to foundation models: a comprehensive review of machine learning approaches for siRNA design.NAR genomics and bioinformatics · 2026Review
- Recent advances in antiviral drugs for Chikungunya virus (CHIKV): Targets, mechanisms, and development strategies.Acta pharmaceutica Sinica. B · 2026Review
- Evolution of siRNA Therapeutics: From Mechanistic Foundations to Clinical Expansion.Pharmaceutics · 2026Review
- Strategic Computational Design of siRNA Molecules Targeting Structural Genes of SARS-CoV-2.Applied biochemistry and biotechnology · 2026Article
- Leveraging Foundation Models for the Characterization of Small-RNA Properties.Computational and structural biotechnology journal · 2026Article
- SiaRNA: a siamese neural network with bidirectional cross-attention for pairwise siRNA-mRNA efficacy prediction.Frontiers in bioinformatics · 2026Article
- shRNAI: A deep neural network for the design of highly potent shRNAs.Molecular therapy. Nucleic acids · 2025Article
- ASOptimizer: optimizing chemical diversity of antisense oligonucleotides through deep learning.Nucleic acids research · 2025Article
- Design, pharmacology, and toxicology of a novel chemically modified siRNA targeting hepatic angiotensinogen.Molecular therapy. Nucleic acids · 2025Article
- Inhibition of Hepatitis B Virus Replication by a Novel GalNAc-siRNA In Vivo and In Vitro.ACS omega · 2025Article
- In Silico and In Vitro development of novel small interfering RNAs (siRNAs) to inhibit SARS-CoV-2.Computational and structural biotechnology journal · 2025Article
- siRNAEfficacyDB: An experimentally supported small interfering RNA efficacy database.IET systems biology · 2024Article
- OligoFormer: an accurate and robust prediction method for siRNA design.Bioinformatics (Oxford, England) · 2024Article
- siRNADiscovery: a graph neural network for siRNA efficacy prediction via deep RNA sequence analysis.Briefings in bioinformatics · 2024Article
- Design of antiviral AGO2-dependent short hairpin RNAs.Virologica Sinica · 2024Article
- ASOptimizer: Optimizing antisense oligonucleotides through deep learning for IDO1 gene regulation.Molecular therapy. Nucleic acids · 2024Article
- RNAi-based drug design: considerations and future directions.Nature reviews. Drug discovery · 2024Review
- Asymmetric trichotomous partitioning overcomes dataset limitations in building machine learning models for predicting siRNA efficacy.Molecular therapy. Nucleic acids · 2023Article
- Toward learning the rules that predict siRNA efficacy.Molecular therapy. Nucleic acids · 2023Article
100 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
- Commented on by
- Erratum issued
- Erratum issued
Authors and funding
14 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The largest gene knock-down experiments performed to date have used multiple short interfering/short hairpin (si/sh)RNAs per gene. To overcome this burden for design of a genome-wide siRNA library, we used the Stuttgart Neural Net Simulator to train algorithms on a data set of 2,182 randomly selected siRNAs targeted to 34 mRNA species, assayed through a high-throughput fluorescent reporter gene system. The algorithm, (BIOPREDsi), reliably predicted activity of 249 siRNAs of an independent test set (Pearson coefficient r = 0.66) and siRNAs targeting endogenous genes at mRNA and protein levels. Neural networks trained on a complementary 21-nucleotide (nt) guide sequence were superior to those trained on a 19-nt sequence. BIOPREDsi was used in the design of a genome-wide siRNA collection with two potent siRNAs per gene. When this collection of 50,000 siRNAs was used to identify genes involved in the cellular response to hypoxia, two of the most potent hits were the key hypoxia transcription factors HIF1A and ARNT.
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What OpenQuestion holds
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.