Prediction of potent shRNAs with a sequential classification algorithm.
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ABSTRACT:
SUBMITTER: Pelossof R
PROVIDER: S-EPMC5416823 | biostudies-literature | 2017 Apr
REPOSITORIES: biostudies-literature
Publications
Prediction of potent shRNAs with a sequential classification algorithm.
Pelossof Raphael R Fairchild Lauren L Huang Chun-Hao CH Widmer Christian C Sreedharan Vipin T VT Sinha Nishi N Lai Dan-Yu DY Guan Yuanzhe Y Premsrirut Prem K PK Tschaharganeh Darjus F DF Hoffmann Thomas T Thapar Vishal V Xiang Qing Q Garippa Ralph J RJ Rätsch Gunnar G Zuber Johannes J Lowe Scott W SW Leslie Christina S CS Fellmann Christof C
Nature biotechnology 20170306 4
We present SplashRNA, a sequential classifier to predict potent microRNA-based short hairpin RNAs (shRNAs). Trained on published and novel data sets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a given gene. Combined with an optimized miR-E backbone, >90% of high-scoring SplashRNA predictions trigger >85% protein knockdown when expressed from a single genomic integration. SplashRNA can significantly improve the accuracy of loss-of-function geneti ...[more]
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