FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2808035226> ?p ?o ?g. }

• W2808035226 abstract "Abstract One of the major challenges in the current drug discovery is the improvement of the docking‐based virtual screening performance. It is especially important in the rational design of compounds with desired polypharmacology or selectivity profiles. To address this problem, we present a methodology for the development of target‐specific scoring functions possessing high screening power. These scoring functions were built using the machine learning methods for the dual target inhibitors of PI3Kα and tankyrase, promising targets for colorectal cancer therapy. The Deep Neural Network models achieve the external test AUC ROC values of 0.96 and 0.93 for the random split and 0.90 and 0.84 for the time‐based split of the PI3Kα and tankyrase inhibitors, respectively. In addition, the impact of the training set size and the actives/decoys ratio on the model quality was assessed. The study demonstrates that the optimized scoring functions could significantly improve the docking screening power for each individual target. This is very useful in the design of multitarget or selective drugs wherein the screening filters are applied in sequence." @default.
• W2808035226 created "2018-06-21" @default.
• W2808035226 creator A5037254457 @default.
• W2808035226 creator A5050532377 @default.
• W2808035226 creator A5055921501 @default.
• W2808035226 creator A5088147889 @default.
• W2808035226 date "2018-06-14" @default.
• W2808035226 modified "2023-09-30" @default.
• W2808035226 title "Machine Learning Classification Models to Improve the Docking-based Screening: A Case of PI3K-Tankyrase Inhibitors" @default.
• W2808035226 cites W1544009106 @default.
• W2808035226 cites W1831050183 @default.
• W2808035226 cites W1968319881 @default.
• W2808035226 cites W1974324284 @default.
• W2808035226 cites W1984673823 @default.
• W2808035226 cites W2019678805 @default.
• W2808035226 cites W2028629022 @default.
• W2808035226 cites W2028857537 @default.
• W2808035226 cites W2030286884 @default.
• W2808035226 cites W2033591223 @default.
• W2808035226 cites W2036438585 @default.
• W2808035226 cites W2038561883 @default.
• W2808035226 cites W2039944201 @default.
• W2808035226 cites W2052460962 @default.
• W2808035226 cites W2059885812 @default.
• W2808035226 cites W2073021822 @default.
• W2808035226 cites W2096171021 @default.
• W2808035226 cites W2132629607 @default.
• W2808035226 cites W2134967712 @default.
• W2808035226 cites W2137048819 @default.
• W2808035226 cites W2278513493 @default.
• W2808035226 cites W2329046360 @default.
• W2808035226 cites W2336817903 @default.
• W2808035226 cites W2340782621 @default.
• W2808035226 cites W2346089935 @default.
• W2808035226 cites W2388080941 @default.
• W2808035226 cites W2416913394 @default.
• W2808035226 cites W2550887636 @default.
• W2808035226 cites W2558999090 @default.
• W2808035226 cites W2586236648 @default.
• W2808035226 cites W2587615823 @default.
• W2808035226 cites W2608559058 @default.
• W2808035226 cites W2623495050 @default.
• W2808035226 cites W2626090269 @default.
• W2808035226 cites W2729949860 @default.
• W2808035226 cites W2740946158 @default.
• W2808035226 cites W2750247885 @default.
• W2808035226 cites W2752378015 @default.
• W2808035226 cites W2756186244 @default.
• W2808035226 cites W2767684755 @default.
• W2808035226 cites W2773532695 @default.
• W2808035226 cites W2782408936 @default.
• W2808035226 cites W2791704581 @default.
• W2808035226 cites W3100704554 @default.
• W2808035226 cites W3104705366 @default.
• W2808035226 cites W4294214970 @default.
• W2808035226 cites W946020316 @default.
• W2808035226 doi "https://doi.org/10.1002/minf.201800030" @default.
• W2808035226 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29901257" @default.
• W2808035226 hasPublicationYear "2018" @default.
• W2808035226 type Work @default.
• W2808035226 sameAs 2808035226 @default.
• W2808035226 citedByCount "22" @default.
• W2808035226 countsByYear W28080352262019 @default.
• W2808035226 countsByYear W28080352262020 @default.
• W2808035226 countsByYear W28080352262021 @default.
• W2808035226 countsByYear W28080352262022 @default.
• W2808035226 countsByYear W28080352262023 @default.
• W2808035226 crossrefType "journal-article" @default.
• W2808035226 hasAuthorship W2808035226A5037254457 @default.
• W2808035226 hasAuthorship W2808035226A5050532377 @default.
• W2808035226 hasAuthorship W2808035226A5055921501 @default.
• W2808035226 hasAuthorship W2808035226A5088147889 @default.
• W2808035226 hasConcept C103697762 @default.
• W2808035226 hasConcept C119857082 @default.
• W2808035226 hasConcept C154945302 @default.
• W2808035226 hasConcept C159110408 @default.
• W2808035226 hasConcept C169258074 @default.
• W2808035226 hasConcept C169903167 @default.
• W2808035226 hasConcept C41008148 @default.
• W2808035226 hasConcept C41685203 @default.
• W2808035226 hasConcept C60644358 @default.
• W2808035226 hasConcept C71924100 @default.
• W2808035226 hasConcept C74187038 @default.
• W2808035226 hasConcept C86803240 @default.
• W2808035226 hasConceptScore W2808035226C103697762 @default.
• W2808035226 hasConceptScore W2808035226C119857082 @default.
• W2808035226 hasConceptScore W2808035226C154945302 @default.
• W2808035226 hasConceptScore W2808035226C159110408 @default.
• W2808035226 hasConceptScore W2808035226C169258074 @default.
• W2808035226 hasConceptScore W2808035226C169903167 @default.
• W2808035226 hasConceptScore W2808035226C41008148 @default.
• W2808035226 hasConceptScore W2808035226C41685203 @default.
• W2808035226 hasConceptScore W2808035226C60644358 @default.
• W2808035226 hasConceptScore W2808035226C71924100 @default.
• W2808035226 hasConceptScore W2808035226C74187038 @default.
• W2808035226 hasConceptScore W2808035226C86803240 @default.
• W2808035226 hasIssue "11" @default.
• W2808035226 hasLocation W28080352261 @default.
• W2808035226 hasLocation W28080352262 @default.
• W2808035226 hasOpenAccess W2808035226 @default.

• next