Matches in SemOpenAlex for { <https://semopenalex.org/work/W3178118856> ?p ?o ?g. }
Showing items 1 to 84 of
84
with 100 items per page.
- W3178118856 abstract "Abstract Motivation Sizeable research has been conducted to facilitate the usage of CRISPR-Cas systems in genome editing, in which deep learning-based methods among others have shown great promise in the prediction of the gRNA efficiency. An accurate prediction of gRNA efficiency helps practitioners optimize their engineered gRNAs, maximizing the on-target efficiency, and minimizing the off-target effects. However, the black box prediction of deep learning-based methods does not provide adequate explanation to the factors that make a sequence efficient; rectifying this issue can help promote the usage of CRISPR-Cas systems in numerous domains. Results We put forward a framework for interpreting gRNA efficiency prediction, dubbed CRISPR-VAE, and apply it to CRISPR/Cpf1. We thus help open the door to a better interpretability of the factors that make a certain gRNA efficient. We further lay out a semantic articulation of such factors into position-wise k-mer rules. The paradigm consists of building an efficiency-aware gRNA sequence generator trained on available real data, and using it to generate a large amount of synthetic sequences with favorable traits, upon which the explanation of the gRNA prediction is based. CRISPR-VAE can further be used as a standalone sequence generator, where the user has access to a low-level editing control. The framework can be readily integrated with different CRISPR-Cas tools and datasets, and its efficacy is confirmed in this paper. Availability and implementation The source code will be shared publicly upon acceptance. Contact ahmad.obeid@ku.ac.ae Index Terms CRISPR, Explainable deep learning" @default.
- W3178118856 created "2021-07-19" @default.
- W3178118856 creator A5006741258 @default.
- W3178118856 creator A5039410837 @default.
- W3178118856 date "2021-07-06" @default.
- W3178118856 modified "2023-09-27" @default.
- W3178118856 title "CRISPR-VAE: A Method for Explaining CRISPR/Cas12a Predictions, and an Efficiency-aware gRNA Sequence Generator" @default.
- W3178118856 cites W1879165674 @default.
- W3178118856 cites W1972476556 @default.
- W3178118856 cites W2058792860 @default.
- W3178118856 cites W2064815984 @default.
- W3178118856 cites W2154598603 @default.
- W3178118856 cites W2166802172 @default.
- W3178118856 cites W2295107390 @default.
- W3178118856 cites W2765284830 @default.
- W3178118856 cites W2786426577 @default.
- W3178118856 cites W2891210592 @default.
- W3178118856 cites W2943243904 @default.
- W3178118856 cites W2953155660 @default.
- W3178118856 cites W2989794628 @default.
- W3178118856 cites W3004378293 @default.
- W3178118856 cites W3005962315 @default.
- W3178118856 cites W3013096400 @default.
- W3178118856 cites W3026538346 @default.
- W3178118856 cites W3087701445 @default.
- W3178118856 cites W3133006703 @default.
- W3178118856 cites W3134782704 @default.
- W3178118856 doi "https://doi.org/10.1101/2021.07.05.451176" @default.
- W3178118856 hasPublicationYear "2021" @default.
- W3178118856 type Work @default.
- W3178118856 sameAs 3178118856 @default.
- W3178118856 citedByCount "0" @default.
- W3178118856 crossrefType "posted-content" @default.
- W3178118856 hasAuthorship W3178118856A5006741258 @default.
- W3178118856 hasAuthorship W3178118856A5039410837 @default.
- W3178118856 hasConcept C104317684 @default.
- W3178118856 hasConcept C121332964 @default.
- W3178118856 hasConcept C124101348 @default.
- W3178118856 hasConcept C144501496 @default.
- W3178118856 hasConcept C154945302 @default.
- W3178118856 hasConcept C163258240 @default.
- W3178118856 hasConcept C2778112365 @default.
- W3178118856 hasConcept C2780992000 @default.
- W3178118856 hasConcept C2781067378 @default.
- W3178118856 hasConcept C41008148 @default.
- W3178118856 hasConcept C54355233 @default.
- W3178118856 hasConcept C62520636 @default.
- W3178118856 hasConcept C70721500 @default.
- W3178118856 hasConcept C86803240 @default.
- W3178118856 hasConcept C97702854 @default.
- W3178118856 hasConcept C98108389 @default.
- W3178118856 hasConceptScore W3178118856C104317684 @default.
- W3178118856 hasConceptScore W3178118856C121332964 @default.
- W3178118856 hasConceptScore W3178118856C124101348 @default.
- W3178118856 hasConceptScore W3178118856C144501496 @default.
- W3178118856 hasConceptScore W3178118856C154945302 @default.
- W3178118856 hasConceptScore W3178118856C163258240 @default.
- W3178118856 hasConceptScore W3178118856C2778112365 @default.
- W3178118856 hasConceptScore W3178118856C2780992000 @default.
- W3178118856 hasConceptScore W3178118856C2781067378 @default.
- W3178118856 hasConceptScore W3178118856C41008148 @default.
- W3178118856 hasConceptScore W3178118856C54355233 @default.
- W3178118856 hasConceptScore W3178118856C62520636 @default.
- W3178118856 hasConceptScore W3178118856C70721500 @default.
- W3178118856 hasConceptScore W3178118856C86803240 @default.
- W3178118856 hasConceptScore W3178118856C97702854 @default.
- W3178118856 hasConceptScore W3178118856C98108389 @default.
- W3178118856 hasLocation W31781188561 @default.
- W3178118856 hasOpenAccess W3178118856 @default.
- W3178118856 hasPrimaryLocation W31781188561 @default.
- W3178118856 hasRelatedWork W2134298288 @default.
- W3178118856 hasRelatedWork W2305742620 @default.
- W3178118856 hasRelatedWork W2951741674 @default.
- W3178118856 hasRelatedWork W2952884279 @default.
- W3178118856 hasRelatedWork W2989961838 @default.
- W3178118856 hasRelatedWork W2994205747 @default.
- W3178118856 hasRelatedWork W3133668443 @default.
- W3178118856 hasRelatedWork W3134782704 @default.
- W3178118856 hasRelatedWork W4225407011 @default.
- W3178118856 hasRelatedWork W4312914540 @default.
- W3178118856 isParatext "false" @default.
- W3178118856 isRetracted "false" @default.
- W3178118856 magId "3178118856" @default.
- W3178118856 workType "article" @default.