2021
DOI: 10.1007/s11103-020-01102-y
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sgRNACNN: identifying sgRNA on-target activity in four crops using ensembles of convolutional neural networks

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Cited by 99 publications
(33 citation statements)
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“…Furthermore, metallic NPs might exert synergistic effects when combined with anticancer drugs [45][46][47]. Guo et al showed that Ni NPs significantly enhance the permeability of cancerous SMMC-7721 hepatocellular carcinoma cells and increase the accumulation of quercetin in these cells [48].…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, metallic NPs might exert synergistic effects when combined with anticancer drugs [45][46][47]. Guo et al showed that Ni NPs significantly enhance the permeability of cancerous SMMC-7721 hepatocellular carcinoma cells and increase the accumulation of quercetin in these cells [48].…”
Section: Discussionmentioning
confidence: 99%
“…The NBC platform technology has the potential to be used in the development of point-of-care diagnostics for pathogen detection and disease management in developed and developing countries [132]. Of course, new simulation and machine learning approaches can help better optimize these devices [133][134][135]. The schematic representation of the current analytical methods and POC devices applied for the detection of E. coli are shown in Figure 11.…”
Section: Point Of Care (Poc) Devices For Clinical Applicationsmentioning
confidence: 99%
“…Beyond modifying Cas9 to generate specific types of edits, predicting the on-target efficiency and off-target effects of particular sgRNAs remains challenging. Recently, however, machine learning approaches have been developed to more efficiently predict these two parameters, and can reduce the guesswork required when designing efficient sgRNAs [ 91 , 92 ].…”
Section: Challenges and Emerging Technologies For Crispr/cas9-based Crop Improvementmentioning
confidence: 99%