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dc.contributor.authorJarada, Tamer N.
dc.contributor.authorRokne, Jon George
dc.contributor.authorAlhajj, Reda
dc.date.accessioned2020-08-21T06:11:46Z
dc.date.available2020-08-21T06:11:46Z
dc.date.issued2020en_US
dc.identifier.citationJarada, T. N., Rokne, J. G. ve Alhajj, R. (2020). A review of computational drug repositioning: Strategies, approaches, opportunities, challenges, and directions. Journal of Cheminformatics, 12(1). https://dx.doi.org/10.1186/s13321-020-00450-7en_US
dc.identifier.issn1758-2946
dc.identifier.urihttps://dx.doi.org/10.1186/s13321-020-00450-7
dc.identifier.urihttps://hdl.handle.net/20.500.12511/5746
dc.description.abstractDrug repositioning is the process of identifying novel therapeutic potentials for existing drugs and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an important role in optimizing the pre-clinical process of developing novel drugs by saving time and cost compared to the traditional de novo drug discovery processes. Since drug repositioning relies on data for existing drugs and diseases the enormous growth of publicly available large-scale biological, biomedical, and electronic health-related data along with the high-performance computing capabilities have accelerated the development of computational drug repositioning approaches. Multidisciplinary researchers and scientists have carried out numerous attempts, with different degrees of efficiency and success, to computationally study the potential of repositioning drugs to identify alternative drug indications. This study reviews recent advancements in the field of computational drug repositioning. First, we highlight different drug repositioning strategies and provide an overview of frequently used resources. Second, we summarize computational approaches that are extensively used in drug repositioning studies. Third, we present different computing and experimental models to validate computational methods. Fourth, we address prospective opportunities, including a few target areas. Finally, we discuss challenges and limitations encountered in computational drug repositioning and conclude with an outline of further research directions.en_US
dc.language.isoengen_US
dc.publisherBMCen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectComputational Drug Repositioningen_US
dc.subjectDrug Repositioning Strategiesen_US
dc.subjectData Miningen_US
dc.subjectMachine Learningen_US
dc.subjectNetwork Analysisen_US
dc.titleA review of computational drug repositioning: Strategies, approaches, opportunities, challenges, and directionsen_US
dc.typereviewen_US
dc.relation.journalJournal of Cheminformaticsen_US
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.authorid0000-0001-6657-9738en_US
dc.identifier.volume12en_US
dc.identifier.issue1en_US
dc.relation.publicationcategoryDiğeren_US
dc.identifier.doi10.1186/s13321-020-00450-7en_US


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