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siRNA - Small Interfering RNAs

siRNA - Small Interfering RNAs

Small interfering RNAs, or siRNAs, are short regulatory RNA molecules that can silence genes post-transcriptionally, as well as the transcriptional level in some cases. siRNAs are important for protecting cells against viral infections and silencing transposable genetic elements.
In the cytoplasm, siRNA is processed from a double-stranded RNA, which comes from either endogenous DNA transcription or exogenous sources like a virus. This double-stranded RNA is then cleaved by the ATP-dependent...

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Related Experiment Video

Updated: Jun 21, 2026

Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins

Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins

Published on: August 9, 2019

Selecting effective siRNA target sequences by using Bayes' theorem.

Shigeru Takasaki¹

¹Toyo University, 1-1-1 Izumino Itakura-machi, Ora-gun, Gunma 374-0193, Japan. s takasaki@toyonet.toyo.ac.jp

Computational Biology and Chemistry

|August 18, 2009

Summary

This summary is machine-generated.

This study introduces a new method using Bayes' theorem to predict the effectiveness of short interfering RNA (siRNA) sequences for gene silencing. The approach improves the selection of potent siRNA for mammalian gene research.

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MISSION esiRNA for RNAi Screening in Mammalian Cells

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Area of Science:

Molecular Biology
Bioinformatics
Genetics

Background:

Short interfering RNA (siRNA) is crucial for studying gene function in mammalian cells.
Current siRNA design rules lack consistency and predictive power for gene silencing efficacy.
Existing methods struggle to estimate the probability of a candidate siRNA sequence effectively silencing a target gene.

Purpose of the Study:

To develop an analytical prediction method for selecting effective siRNA target sequences.
To address the limitations of existing score-based siRNA design techniques.
To provide a probabilistic estimate of siRNA efficacy for mammalian gene targets.

Main Methods:

Application of Bayes' theorem for analytical prediction of siRNA effectiveness.
Development of a novel method distinct from previous score-based approaches.
Evaluation using recently reported effective and ineffective siRNA sequences across various genes.

Main Results:

The proposed Bayes' theorem-based method can predict the probability of siRNA sequence effectiveness.
The method demonstrates utility across a range of mammalian genes.
It offers a more reliable approach compared to existing design guidelines.

Conclusions:

The developed analytical prediction method is effective for selecting functional siRNA sequences.
This approach enhances the reliability of siRNA-mediated gene silencing in mammalian systems.
It provides a valuable tool for researchers in gene function studies.