Matches in SemOpenAlex for { <https://semopenalex.org/work/W2891868449> ?p ?o ?g. }
- W2891868449 endingPage "4405" @default.
- W2891868449 startingPage "4398" @default.
- W2891868449 abstract "Modern computational approaches and machine learning techniques accelerate the invention of new drugs. Generative models can discover novel molecular structures within hours, while conventional drug discovery pipelines require months of work. In this article, we propose a new generative architecture, entangled conditional adversarial autoencoder, that generates molecular structures based on various properties, such as activity against a specific protein, solubility, or ease of synthesis. We apply the proposed model to generate a novel inhibitor of Janus kinase 3, implicated in rheumatoid arthritis, psoriasis, and vitiligo. The discovered molecule was tested in vitro and showed good activity and selectivity." @default.
- W2891868449 created "2018-09-27" @default.
- W2891868449 creator A5001033487 @default.
- W2891868449 creator A5013472071 @default.
- W2891868449 creator A5019867253 @default.
- W2891868449 creator A5020792131 @default.
- W2891868449 creator A5028940329 @default.
- W2891868449 creator A5031083770 @default.
- W2891868449 creator A5032823970 @default.
- W2891868449 creator A5050327613 @default.
- W2891868449 creator A5061298160 @default.
- W2891868449 creator A5083789823 @default.
- W2891868449 date "2018-09-04" @default.
- W2891868449 modified "2023-10-18" @default.
- W2891868449 title "Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery" @default.
- W2891868449 cites W1975147762 @default.
- W2891868449 cites W1979320823 @default.
- W2891868449 cites W2016589492 @default.
- W2891868449 cites W2038702914 @default.
- W2891868449 cites W2044834685 @default.
- W2891868449 cites W2131923232 @default.
- W2891868449 cites W2134967712 @default.
- W2891868449 cites W2158156131 @default.
- W2891868449 cites W2160592148 @default.
- W2891868449 cites W2290847742 @default.
- W2891868449 cites W2306570595 @default.
- W2891868449 cites W2399240576 @default.
- W2891868449 cites W2502949459 @default.
- W2891868449 cites W2515779400 @default.
- W2891868449 cites W2524827175 @default.
- W2891868449 cites W2553304123 @default.
- W2891868449 cites W2556070101 @default.
- W2891868449 cites W2558999090 @default.
- W2891868449 cites W2566974850 @default.
- W2891868449 cites W2567534979 @default.
- W2891868449 cites W2578240541 @default.
- W2891868449 cites W2610148085 @default.
- W2891868449 cites W2610332124 @default.
- W2891868449 cites W2765224015 @default.
- W2891868449 cites W2767394258 @default.
- W2891868449 cites W2789074794 @default.
- W2891868449 cites W2790808809 @default.
- W2891868449 cites W2793945656 @default.
- W2891868449 cites W2805002767 @default.
- W2891868449 cites W2883583109 @default.
- W2891868449 cites W2951934944 @default.
- W2891868449 cites W2963445908 @default.
- W2891868449 cites W3098269892 @default.
- W2891868449 cites W3104705366 @default.
- W2891868449 doi "https://doi.org/10.1021/acs.molpharmaceut.8b00839" @default.
- W2891868449 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30180591" @default.
- W2891868449 hasPublicationYear "2018" @default.
- W2891868449 type Work @default.
- W2891868449 sameAs 2891868449 @default.
- W2891868449 citedByCount "157" @default.
- W2891868449 countsByYear W28918684492018 @default.
- W2891868449 countsByYear W28918684492019 @default.
- W2891868449 countsByYear W28918684492020 @default.
- W2891868449 countsByYear W28918684492021 @default.
- W2891868449 countsByYear W28918684492022 @default.
- W2891868449 countsByYear W28918684492023 @default.
- W2891868449 crossrefType "journal-article" @default.
- W2891868449 hasAuthorship W2891868449A5001033487 @default.
- W2891868449 hasAuthorship W2891868449A5013472071 @default.
- W2891868449 hasAuthorship W2891868449A5019867253 @default.
- W2891868449 hasAuthorship W2891868449A5020792131 @default.
- W2891868449 hasAuthorship W2891868449A5028940329 @default.
- W2891868449 hasAuthorship W2891868449A5031083770 @default.
- W2891868449 hasAuthorship W2891868449A5032823970 @default.
- W2891868449 hasAuthorship W2891868449A5050327613 @default.
- W2891868449 hasAuthorship W2891868449A5061298160 @default.
- W2891868449 hasAuthorship W2891868449A5083789823 @default.
- W2891868449 hasBestOaLocation W28918684491 @default.
- W2891868449 hasConcept C101738243 @default.
- W2891868449 hasConcept C103637391 @default.
- W2891868449 hasConcept C108583219 @default.
- W2891868449 hasConcept C119857082 @default.
- W2891868449 hasConcept C154945302 @default.
- W2891868449 hasConcept C2780035454 @default.
- W2891868449 hasConcept C39890363 @default.
- W2891868449 hasConcept C41008148 @default.
- W2891868449 hasConcept C60644358 @default.
- W2891868449 hasConcept C70721500 @default.
- W2891868449 hasConcept C74187038 @default.
- W2891868449 hasConcept C86803240 @default.
- W2891868449 hasConcept C98274493 @default.
- W2891868449 hasConceptScore W2891868449C101738243 @default.
- W2891868449 hasConceptScore W2891868449C103637391 @default.
- W2891868449 hasConceptScore W2891868449C108583219 @default.
- W2891868449 hasConceptScore W2891868449C119857082 @default.
- W2891868449 hasConceptScore W2891868449C154945302 @default.
- W2891868449 hasConceptScore W2891868449C2780035454 @default.
- W2891868449 hasConceptScore W2891868449C39890363 @default.
- W2891868449 hasConceptScore W2891868449C41008148 @default.
- W2891868449 hasConceptScore W2891868449C60644358 @default.
- W2891868449 hasConceptScore W2891868449C70721500 @default.
- W2891868449 hasConceptScore W2891868449C74187038 @default.
- W2891868449 hasConceptScore W2891868449C86803240 @default.