Prediction of potent shRNAs with a sequential classification algorithm
| العنوان: | Prediction of potent shRNAs with a sequential classification algorithm |
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| المؤلفون: | Raphael Pelossof, Christof Fellmann, Qing Xiang, Darjus F. Tschaharganeh, Thomas Hoffmann, Vishal Thapar, Christina S. Leslie, Johannes Zuber, Ralph Garippa, Scott W. Lowe, Yuanzhe Guan, Chun-Hao Huang, Gunnar Rätsch, Nishi Sinha, Prem K. Premsrirut, Christian Widmer, Lauren Fairchild, Dan-Yu Lai, Vipin T. Sreedharan |
| المصدر: | Nature biotechnology |
| بيانات النشر: | Springer Science and Business Media LLC, 2017. |
| سنة النشر: | 2017 |
| مصطلحات موضوعية: | 0301 basic medicine, Computer science, Biomedical Engineering, Bioengineering, Applied Microbiology and Biotechnology, Article, Machine Learning, Small hairpin RNA, 03 medical and health sciences, RNA interference, microRNA, Gene silencing, Clustered Regularly Interspaced Short Palindromic Repeats, Gene Silencing, RNA, Small Interfering, Gene knockdown, Sequence Analysis, RNA, Extramural, Chromosome Mapping, 030104 developmental biology, Cancer genetics, Molecular Medicine, CRISPR-Cas Systems, Algorithm, Algorithms, Software, Biotechnology |
| الوصف: | 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. |
| تدمد: | 1546-1696 1087-0156 |
| DOI: | 10.1038/nbt.3807 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::882a7982313d98863f3c1a8eae92ab82 https://doi.org/10.1038/nbt.3807 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....882a7982313d98863f3c1a8eae92ab82 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15461696 10870156 |
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| DOI: | 10.1038/nbt.3807 |