An accurate and interpretable model for siRNA efficacy prediction.
An accurate and interpretable model for siRNA efficacy prediction.
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DOI：
10.1186/1471-2105-7-520
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发表时间：
2006-11-30
影响因子：
3
通讯作者：
Vandenbrouck Y
中科院分区：
文献类型：
--
作者：
Vert JP;Foveau N;Lajaunie C;Vandenbrouck Y
使用外源小干扰RNA（siRNA）进行基因沉默已迅速成为一种广泛使用的分子工具，为基因功能研究和新药靶点识别提供了有力的手段。尽管最近在了解 RNAi 途径如何介导基因沉默方面取得了相当大的进展，但有效 siRNA 的设计仍然具有挑战性。我们提出了一个结合 siRNA 序列基本特征的简单线性模型，用于 siRNA 功效预测。它在最近提供的 siRNA 序列大型数据集上进行了训练和测试，在效力预测准确性方面表现与更复杂的最先进模型一样，并具有可直接解释的优点。该线性模型的分析使我们能够检测和量化特定位置的核苷酸偏好的影响，包括先前已知的和新的观察结果。我们还检测并量化了强效siRNA在其序列中包含短不对称基序的强烈倾向，并且令人惊讶地表明，这些基序单独包含至少与特定位置的核苷酸偏好一样多的效力预测相关信息。为预测 siRNA 效力而提出的模型与最先进的非线性模型一样准确，并且在生物学特征方面很容易解释。它可以在网上免费获得：
The use of exogenous small interfering RNAs (siRNAs) for gene silencing has quickly become a widespread molecular tool providing a powerful means for gene functional study and new drug target identification. Although considerable progress has been made recently in understanding how the RNAi pathway mediates gene silencing, the design of potent siRNAs remains challenging. We propose a simple linear model combining basic features of siRNA sequences for siRNA efficacy prediction. Trained and tested on a large dataset of siRNA sequences made recently available, it performs as well as more complex state-of-the-art models in terms of potency prediction accuracy, with the advantage of being directly interpretable. The analysis of this linear model allows us to detect and quantify the effect of nucleotide preferences at particular positions, including previously known and new observations. We also detect and quantify a strong propensity of potent siRNAs to contain short asymmetric motifs in their sequence, and show that, surprisingly, these motifs alone contain at least as much relevant information for potency prediction as the nucleotide preferences for particular positions. The model proposed for prediction of siRNA potency is as accurate as a state-of-the-art nonlinear model and is easily interpretable in terms of biological features. It is freely available on the web at
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影响因子：
46.9
作者：
Jackson, AL;Bartz, SR;Linsley, PS
通讯作者：
Linsley, PS
影响因子：
14.9
作者：
Ding, Y;Chan, CY;Lawrence, CE
通讯作者：
Lawrence, CE
影响因子：
16.8
作者：
Haley, B;Zamore, PD
通讯作者：
Zamore, PD
DOI：
10.1073/pnas.83.24.9373
发表时间：
1986-12-01
影响因子：
11.1
作者：
FREIER, SM;KIERZEK, R;TURNER, DH
通讯作者：
TURNER, DH
影响因子：
14.9
作者：
Heale BS;Soifer HS;Bowers C;Rossi JJ
通讯作者：
Rossi JJ