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Akademický článek

Deep learning improves the ability of sgRNA off-target propensity prediction

Autor: Qiaoyue Liu, Xiang Cheng, Gan Liu, Bohao Li, Xiuqin Liu

Publikováno v: BMC Bioinformatics, Vol 21, Iss 1, Pp 1-15 (2020)

Abstract Background CRISPR/Cas9 system, as the third-generation genome editing technology, has been widely applied in target gene repair and gene expression regulation. Selection of appropriate sgRNA can improve the on-target knockout efficacy of CRI

Externí odkaz: https://doaj.org/article/424a9676b01841b09a34fd82edad48f3

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Invoice Detection and Classification based on Improved YOLOv5s

Autor: Weihua Niu, Qiaoyue Liu

Publikováno v: Scientific Journal of Technology. 5:39-48

For the complex problems of invoice occlusion, invoice deformation, dark environment, excessive noise and so on in invoice detection, this paper proposes an improved YOLOv5s invoice detection and classification method. In order to improve the general

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cf75b5f1f758259f04d4065c3c7258a1
https://doi.org/10.54691/sjt.v5i4.4737

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A novel numerical model for investigating macro factors influencing building energy consumption intensity

Autor: Qiaoyue Liu, Yafeng Gao, Wei Feng, Jinxin Huang, Dachuan Shi, Xiuyuan Du, Changqing Lin

Publikováno v: Sustainable Production and Consumption. 24:308-323

Building energy use accounts for 40% of the primary energy consumed worldwide. Therefore, it is essential to explore the key influencing factors and the associated interactions among these factors in order to achieve energy-saving goals. In practical

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fccda27f919e34461cc3fd58bd8e4f05
https://doi.org/10.1016/j.spc.2020.07.014

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Deep learning improves the ability of sgRNA off-target propensity prediction

Autor: Bohao Li, Xiuqin Liu, Qiaoyue Liu, Gan Liu, Xiang Cheng

Publikováno v: BMC Bioinformatics, Vol 21, Iss 1, Pp 1-15 (2020)
BMC Bioinformatics

Background CRISPR/Cas9 system, as the third-generation genome editing technology, has been widely applied in target gene repair and gene expression regulation. Selection of appropriate sgRNA can improve the on-target knockout efficacy of CRISPR/Cas9

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e1d6e2c8cc9c52898cce04fbfc02bba
https://doaj.org/article/424a9676b01841b09a34fd82edad48f3

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Additional file 2 of Deep learning improves the ability of sgRNA off-target propensity prediction

Autor: Qiaoyue Liu, Cheng, Xiang, Liu, Gan, Bohao Li, Xiuqin Liu

Additional file 2. A detailed description of the model structure for model selection.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68dfd1068229c3c822f99fae32327788

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Akademický článek

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