Prediction of potent shRNAs with a sequential classification algorithm Journal Article
| Authors: | Pelossof, R.; Fairchild, L.; Huang, C. H.; Widmer, C.; Sreedharan, V. T.; Sinha, N.; Lai, D. Y.; Guan, Y.; Premsrirut, P. K.; Tschaharganeh, D. F.; Hoffmann, T.; Thapar, V.; Xiang, Q.; Garippa, R. J.; Rätsch, G.; Zuber, J.; Lowe, S. W.; Leslie, C. S.; Fellmann, C. |
| Article Title: | Prediction of potent shRNAs with a sequential classification algorithm |
| Abstract: | 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 genetics studies and facilitates the generation of compact shRNA libraries. © 2017 Nature America, Inc. |
| Keywords: | rna; forecasting; micrornas; short hairpin rna; classification algorithm; genomic integration; sequential classifier |
| Journal Title: | Nature Biotechnology |
| Volume: | 35 |
| Issue: | 4 |
| ISSN: | 1087-0156 |
| Publisher: | Nature Publishing Group |
| Date Published: | 2017-04-01 |
| Start Page: | 350 |
| End Page: | 353 |
| Language: | English |
| DOI: | 10.1038/nbt.3807 |
| PROVIDER: | scopus |
| PUBMED: | 28263295 |
| PMCID: | PMC5416823 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 2 May 2017 -- Source: Scopus |
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