Matches in SemOpenAlex for { <https://semopenalex.org/work/W3083005245> ?p ?o ?g. }
Showing items 1 to 55 of
55
with 100 items per page.
- W3083005245 abstract "Abstract Cancers are complex, heterogeneous diseases with limited treatment options. All currently available anticancer drugs have significant drawbacks, partially attributable to the outdated one drug–one gene–one disease paradigm. Polypharmacology, a new paradigm where one drug exerts maximal benefit to the patient by interacting with multiple intended biological targets, has been newly emerged and expected to overcome the limitations. Machine learning methods and their applications have been actively studied in recent years to systematically explore and derive undiscovered knowledge from the large-scale experimental data produced from advanced high-throughput laboratory techniques. This chapter reviews a number of important advancements in data-driven machine learning–based drug repositioning strategies for polypharmacology. We start our discussion from the initial step of data acquisition and preparation, followed by examples of molecular representation and machine learning methods." @default.
- W3083005245 created "2020-09-11" @default.
- W3083005245 creator A5050104020 @default.
- W3083005245 creator A5066245750 @default.
- W3083005245 date "2020-01-01" @default.
- W3083005245 modified "2023-09-27" @default.
- W3083005245 title "Machine learning strategies for identifying repurposed drugs for cancer therapy" @default.
- W3083005245 doi "https://doi.org/10.1016/b978-0-12-819668-7.00003-8" @default.
- W3083005245 hasPublicationYear "2020" @default.
- W3083005245 type Work @default.
- W3083005245 sameAs 3083005245 @default.
- W3083005245 citedByCount "1" @default.
- W3083005245 countsByYear W30830052452021 @default.
- W3083005245 crossrefType "book-chapter" @default.
- W3083005245 hasAuthorship W3083005245A5050104020 @default.
- W3083005245 hasAuthorship W3083005245A5066245750 @default.
- W3083005245 hasConcept C103637391 @default.
- W3083005245 hasConcept C119857082 @default.
- W3083005245 hasConcept C154945302 @default.
- W3083005245 hasConcept C2522767166 @default.
- W3083005245 hasConcept C2780035454 @default.
- W3083005245 hasConcept C41008148 @default.
- W3083005245 hasConcept C60644358 @default.
- W3083005245 hasConcept C71924100 @default.
- W3083005245 hasConcept C74187038 @default.
- W3083005245 hasConcept C86803240 @default.
- W3083005245 hasConcept C98274493 @default.
- W3083005245 hasConceptScore W3083005245C103637391 @default.
- W3083005245 hasConceptScore W3083005245C119857082 @default.
- W3083005245 hasConceptScore W3083005245C154945302 @default.
- W3083005245 hasConceptScore W3083005245C2522767166 @default.
- W3083005245 hasConceptScore W3083005245C2780035454 @default.
- W3083005245 hasConceptScore W3083005245C41008148 @default.
- W3083005245 hasConceptScore W3083005245C60644358 @default.
- W3083005245 hasConceptScore W3083005245C71924100 @default.
- W3083005245 hasConceptScore W3083005245C74187038 @default.
- W3083005245 hasConceptScore W3083005245C86803240 @default.
- W3083005245 hasConceptScore W3083005245C98274493 @default.
- W3083005245 hasLocation W30830052451 @default.
- W3083005245 hasOpenAccess W3083005245 @default.
- W3083005245 hasPrimaryLocation W30830052451 @default.
- W3083005245 hasRelatedWork W10130694 @default.
- W3083005245 hasRelatedWork W10931660 @default.
- W3083005245 hasRelatedWork W11991885 @default.
- W3083005245 hasRelatedWork W12970924 @default.
- W3083005245 hasRelatedWork W13710472 @default.
- W3083005245 hasRelatedWork W4630997 @default.
- W3083005245 hasRelatedWork W6161656 @default.
- W3083005245 hasRelatedWork W7677535 @default.
- W3083005245 hasRelatedWork W8589957 @default.
- W3083005245 hasRelatedWork W8629692 @default.
- W3083005245 isParatext "false" @default.
- W3083005245 isRetracted "false" @default.
- W3083005245 magId "3083005245" @default.
- W3083005245 workType "book-chapter" @default.