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Cited by 293

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

siDirect: highly effective, target-specific siRNA design software for mammalian RNA interference

Open access
Naito, Y., Yamada, T., Ui-Tei, K., Morishita, S., Saigo, K.·2004·Nucleic Acids Research

Abstract

siDirect (http://design.RNAi.jp/) is a web-based online software system for computing highly effective small interfering RNA (siRNA) sequences with maximum target-specificity for mammalian RNA interference (RNAi). Highly effective siRNA sequences are selected using novel guidelines that were established through an extensive study of the relationship between siRNA sequences and RNAi activity. Our efficient software avoids off-target gene silencing to enumerate potential cross-hybridization candidates that the widely used BLAST search may overlook. The website accepts an arbitrary sequence as input and quickly returns siRNA candidates, providing a wide scope of applications in mammalian RNAi, including systematic functional genomics and therapeutic gene silencing.

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Crossref · 10.1093/nar/gkh442

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Metadata

Authors
Naito, Y., Yamada, T., Ui-Tei, K., Morishita, S., & Saigo, K.
Venue
Nucleic Acids Research
Published
2004-07-01
Volume
32
Issue
Web Server
Pages
W124-W129
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W2129205448
Cited by
293
References
21
FWCI
9.51
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: siDirect: highly effective, target-specific siRNA design software for mammalian RNA interference. https://app.cochat.ai/papers/10.1093/nar/gkh442
The paper
Naito, Y., Yamada, T., Ui-Tei, K., Morishita, S., & Saigo, K. (2004). siDirect: highly effective, target-specific siRNA design software for mammalian RNA interference. Nucleic Acids Research. https://doi.org/10.1093/nar/gkh442

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.