{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T08:17:32Z","timestamp":1776068252221,"version":"3.50.1"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T00:00:00Z","timestamp":1664496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100001809","name":"China National Natural Science Foundation","doi-asserted-by":"crossref","award":["62172121"],"award-info":[{"award-number":["62172121"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"China National Natural Science Foundation","doi-asserted-by":"crossref","award":["82073800"],"award-info":[{"award-number":["82073800"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,11,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Short hairpin RNA (shRNA)-mediated gene silencing is an important technology to achieve RNA interference, in which the design of potent and reliable shRNA molecules plays a crucial role. However, efficient shRNA target selection through biological technology is expensive and time consuming. Hence, it is crucial to develop a more precise and efficient computational method to design potent and reliable shRNA molecules. In this work, we present an interpretable classification model for the shRNA target prediction using the Light Gradient Boosting Machine algorithm called ILGBMSH. Rather than utilizing only the shRNA sequence feature, we extracted 554 biological and deep learning features, which were not considered in previous shRNA prediction research. We evaluated the performance of our model compared with the state-of-the-art shRNA target prediction models. Besides, we investigated the feature explanation from the model\u2019s parameters and interpretable method called Shapley Additive Explanations, which provided us with biological insights from the model. We used independent shRNA experiment data from other resources to prove the predictive ability and robustness of our model. Finally, we used our model to design the miR30-shRNA sequences and conducted a gene knockdown experiment. The experimental result was perfectly in correspondence with our expectation with a Pearson\u2019s coefficient correlation of 0.985. In summary, the ILGBMSH model can achieve state-of-the-art shRNA prediction performance and give biological insights from the machine learning model parameters.<\/jats:p>","DOI":"10.1093\/bib\/bbac429","type":"journal-article","created":{"date-parts":[[2022,10,3]],"date-time":"2022-10-03T00:59:20Z","timestamp":1664758760000},"source":"Crossref","is-referenced-by-count":17,"title":["ILGBMSH: an interpretable classification model for the shRNA target prediction with ensemble learning algorithm"],"prefix":"10.1093","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4328-466X","authenticated-orcid":false,"given":"Chengkui","family":"Zhao","sequence":"first","affiliation":[{"name":"Institute of Intelligent System and Bioinformatics, College of Intelligent Systems Science and Engineering, Harbin Engineering University , Harbin 150001 , China"}]},{"given":"Nan","family":"Xu","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Engineering and Technology, Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University , No, 3663 North Zhongshan Road, Shanghai 200065 , China"},{"name":"Shanghai Unicar-Therapy Bio-medicine Technology Co. , Ltd, No 1525 Minqiang Road, Shanghai, 201612 , China"}]},{"given":"Jingwen","family":"Tan","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Engineering and Technology, Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University , No, 3663 North Zhongshan Road, Shanghai 200065 , China"},{"name":"Shanghai Unicar-Therapy Bio-medicine Technology Co. , Ltd, No 1525 Minqiang Road, Shanghai, 201612 , China"}]},{"given":"Qi","family":"Cheng","sequence":"additional","affiliation":[{"name":"Institute of Intelligent System and Bioinformatics, College of Intelligent Systems Science and Engineering, Harbin Engineering University , Harbin 150001 , China"}]},{"given":"Weixin","family":"Xie","sequence":"additional","affiliation":[{"name":"Institute of Intelligent System and Bioinformatics, College of Intelligent Systems Science and Engineering, Harbin Engineering University , Harbin 150001 , China"}]},{"given":"Jiayu","family":"Xu","sequence":"additional","affiliation":[{"name":"Institute of Intelligent System and Bioinformatics, College of Intelligent Systems Science and Engineering, Harbin Engineering University , Harbin 150001 , China"}]},{"given":"Zhenyu","family":"Wei","sequence":"additional","affiliation":[{"name":"Institute of Intelligent System and Bioinformatics, College of Intelligent Systems Science and Engineering, Harbin Engineering University , Harbin 150001 , China"}]},{"given":"Jing","family":"Ye","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Engineering and Technology, Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University , No, 3663 North Zhongshan Road, Shanghai 200065 , China"},{"name":"Shanghai Unicar-Therapy Bio-medicine Technology Co. , Ltd, No 1525 Minqiang Road, Shanghai, 201612 , China"}]},{"given":"Lei","family":"Yu","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Engineering and Technology, Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University , No, 3663 North Zhongshan Road, Shanghai 200065 , China"},{"name":"Shanghai Unicar-Therapy Bio-medicine Technology Co. , Ltd, No 1525 Minqiang Road, Shanghai, 201612 , China"}]},{"given":"Weixing","family":"Feng","sequence":"additional","affiliation":[{"name":"Institute of Intelligent System and Bioinformatics, College of Intelligent Systems Science and Engineering, Harbin Engineering University , Harbin 150001 , China"}]}],"member":"286","published-online":{"date-parts":[[2022,9,30]]},"reference":[{"key":"2022112111120488600_ref1","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1007\/978-1-62703-119-6_12","article-title":"Short hairpin RNA-mediated gene silencing","volume":"942","author":"Lambeth","year":"2013","journal-title":"Methods Mol Biol"},{"key":"2022112111120488600_ref2","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1038\/sj.mt.6300382","article-title":"Lentiviral vector design for multiple shRNA expression and durable HIV-1 inhibition","volume":"16","author":"Brake","year":"2008","journal-title":"Mol Ther"},{"key":"2022112111120488600_ref3","doi-asserted-by":"crossref","first-page":"879","DOI":"10.1261\/rna.1977810","article-title":"Reduced seed region-based off-target activity with lentivirus-mediated RNAi","volume":"16","author":"Klinghoffer","year":"2010","journal-title":"RNA"},{"key":"2022112111120488600_ref4","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/1472-6750-6-7","article-title":"Criteria for effective design, construction, and gene knockdown by shRNA vectors","volume":"6","author":"Taxman","year":"2006","journal-title":"BMC Biotechnol"},{"key":"2022112111120488600_ref5","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1016\/j.molcel.2011.02.008","article-title":"Functional identification of optimized RNAi triggers using a massively parallel sensor assay","volume":"41","author":"Fellmann","year":"2011","journal-title":"Mol Cell"},{"key":"2022112111120488600_ref6","doi-asserted-by":"crossref","first-page":"163","DOI":"10.3389\/fgene.2012.00163","article-title":"Optimized models for design of efficient miR30-based shRNAs","volume":"3","author":"Matveeva","year":"2012","journal-title":"Front Genet"},{"key":"2022112111120488600_ref7","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1038\/nbt.3807","article-title":"Prediction of potent shRNAs with a sequential classification algorithm","volume":"35","author":"Pelossof","year":"2017","journal-title":"Nat Biotechnol"},{"key":"2022112111120488600_ref8","first-page":"3149","article-title":"LightGBM: a highly efficient gradient boosting decision tree","volume-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems","author":"Ke","year":"2017"},{"key":"2022112111120488600_ref9","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1186\/s13059-021-02492-y","article-title":"LightGBM: accelerated genomically designed crop breeding through ensemble learning","volume":"22","author":"Yan","year":"2021","journal-title":"Genome Biol"},{"key":"2022112111120488600_ref10","first-page":"4768","volume-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems","author":"Lundberg","year":"2017"},{"key":"2022112111120488600_ref11","first-page":"1","volume-title":"2017 International Conference on Engineering and Technology (ICET)","author":"Albawi","year":"2017"},{"key":"2022112111120488600_ref12","first-page":"1735","article-title":"Long short-term memory","volume-title":"Neural Comput","author":"Hochreiter","year":"1997"},{"key":"2022112111120488600_ref13","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1145\/3359786","article-title":"Techniques for interpretable machine learning","volume":"63","author":"Du","year":"2020","journal-title":"Commun ACM"},{"key":"2022112111120488600_ref14","doi-asserted-by":"crossref","first-page":"358","DOI":"10.2337\/dc20-1536","article-title":"Interpretable machine learning framework reveals robust gut microbiome features associated with type 2 diabetes","volume":"44","author":"Gou","year":"2021","journal-title":"Diabetes Care"},{"key":"2022112111120488600_ref15","first-page":"307","article-title":"Multi-target inhibition by four tandem shRNAs embedded in homo- or hetero-miRNA backbones","volume-title":"Mol Med Rep","author":"Du","year":"2018"},{"key":"2022112111120488600_ref16","doi-asserted-by":"crossref","first-page":"1178","DOI":"10.1261\/rna.7650904","article-title":"Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization","volume":"10","author":"Mathews","year":"2004","journal-title":"RNA"},{"key":"2022112111120488600_ref17","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/S0092-8674(03)00759-1","article-title":"Asymmetry in the assembly of the RNAi enzyme complex","volume":"115","author":"Schwarz","year":"2003","journal-title":"Cell"},{"key":"2022112111120488600_ref18","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkm699","article-title":"Thermodynamic instability of siRNA duplex is a prerequisite for dependable prediction of siRNA activities","volume":"35","author":"Ichihara","year":"2007","journal-title":"Nucleic Acids Res"},{"key":"2022112111120488600_ref19","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1186\/1471-2105-7-65","article-title":"Computational models with thermodynamic and composition features improve siRNA design","volume":"7","author":"Shabalina","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"2022112111120488600_ref20","article-title":"Thermodynamic parameters for an expanded nearest-neighbor model for formation of RNA duplexes with Watson-Crick base pairs","volume-title":"Biochemistry","author":"Xia","year":"1998"},{"key":"2022112111120488600_ref21","doi-asserted-by":"crossref","DOI":"10.1145\/2939672.2939785","article-title":"XGBoost: A scalable tree boosting System","author":"Chen","year":"2016"},{"key":"2022112111120488600_ref22","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy function approximation: a gradient boosting machine","volume":"29","author":"Friedman","year":"2001","journal-title":"Ann Stat"},{"key":"2022112111120488600_ref23","article-title":"Experiments with a new boosting algorithm","author":"Freund","year":"1996","journal-title":"Proceedings of the Thirteenth International Conference on International Conference on Machine Learning (ICML'96)"},{"issue":"1","key":"2022112111120488600_ref24","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","journal-title":"Mach Learn"},{"key":"2022112111120488600_ref25","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1186\/1471-2105-7-520","article-title":"An accurate and interpretable model for siRNA efficacy prediction","volume":"7","author":"Vert","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"2022112111120488600_ref26","doi-asserted-by":"crossref","first-page":"E3384","DOI":"10.1073\/pnas.1508821112","article-title":"Next-generation libraries for robust RNA interference-based genome-wide screens","volume":"112","author":"Kampmann","year":"2015","journal-title":"Proc Natl Acad Sci U S A"},{"key":"2022112111120488600_ref27","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0025642","article-title":"MysiRNA-designer: a workflow for efficient siRNA design","volume":"6","author":"Mysara","year":"2011","journal-title":"PLoS One"},{"key":"2022112111120488600_ref28","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.ygeno.2013.07.009","article-title":"The effect of regions flanking target site on siRNA potency","volume":"102","author":"Liu","year":"2013","journal-title":"Genomics"},{"key":"2022112111120488600_ref29","doi-asserted-by":"crossref","first-page":"6444","DOI":"10.1093\/nar\/gkg876","article-title":"Nucleotide sequence homology requirements of HIV-1-specific short hairpin RNA","volume":"31","author":"Pusch","year":"2003","journal-title":"Nucleic Acids Res"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/23\/6\/bbac429\/47143857\/bbac429.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/23\/6\/bbac429\/47143857\/bbac429.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,21]],"date-time":"2022-11-21T11:18:04Z","timestamp":1669029484000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbac429\/6731717"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,30]]},"references-count":29,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,11,19]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbac429","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,11]]},"published":{"date-parts":[[2022,9,30]]},"article-number":"bbac429"}}