Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8617
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dc.contributor.authorBardak B.-
dc.contributor.authorTan, Mehmet-
dc.date.accessioned2022-07-30T16:43:35Z-
dc.date.available2022-07-30T16:43:35Z-
dc.date.issued2021-
dc.identifier.citationBardak, B., & Tan, M. (2021, October). DeepGREP: A deep convolutional neural network for predicting gene-regulating effects of small molecules. In 2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) (pp. 1-8). IEEE.en_US
dc.identifier.isbn9781665401128-
dc.identifier.urihttps://doi.org/10.1109/CIBCB49929.2021.9562920-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/8617-
dc.description2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2021 -- 13 October 2021 through 15 October 2021 -- -- 176925en_US
dc.description.abstractAccurately predicting desired gene expression effects by using the representations of drugs and genes in silico is a key task in chemogenomics. This paper proposes DeepGREP, a deep learning model that can predict small molecules’ gene regulation effects. The main motivation of this work is improving chemical-induced differential gene expression prediction by using a convolutional-based architecture to represent drugs and genes more effectively. To evaluate the performance of the DeepGREP, we conducted several experiments and compared them with DeepCop, the baseline model. The results show that DeepGREP outperforms the baseline model and significantly improves the gene expression prediction for AUC by around 4%, F-Score by around 15%, and Enrichment Factor by around 22%. We also demonstrate that the proposed method mostly outperforms the baseline in more difficulties setting of generalization to unseen molecules by using cold-drug splitting. © 2021 IEEE.en_US
dc.description.sponsorshipTürkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK: 118E759en_US
dc.description.sponsorshipVI. ACKNOWLEDGEMENTS This study is funded by The Scientific and Technological Research Council of Turkey (Grant No: 118E759)en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2021en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectChemical-induceden_US
dc.subjectDeep neural networksen_US
dc.subjectGene expressionen_US
dc.subjectConvolutionen_US
dc.subjectConvolutional neural networksen_US
dc.subjectDeep neural networksen_US
dc.subjectForecastingen_US
dc.subjectMoleculesen_US
dc.subjectBaseline modelsen_US
dc.subjectChemical-induceden_US
dc.subjectChemogenomicsen_US
dc.subjectDifferential gene expressionsen_US
dc.subjectGene expression effectsen_US
dc.subjectGene-regulationen_US
dc.subjectGenes expressionen_US
dc.subjectIn-silicoen_US
dc.subjectLearning modelsen_US
dc.subjectSmall moleculesen_US
dc.subjectGene expressionen_US
dc.titleDeepGrep: A deep convolutional neural network for predicting gene-regulating effects of small moleculesen_US
dc.typeConference Objecten_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.identifier.wosWOS:000848229700007en_US
dc.identifier.scopus2-s2.0-85126476054en_US
dc.institutionauthorTan, Mehmet-
dc.identifier.doi10.1109/CIBCB49929.2021.9562920-
dc.authorscopusid57188767392-
dc.authorscopusid36984623900-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeConference Object-
item.cerifentitytypePublications-
item.languageiso639-1en-
crisitem.author.dept02.3. Department of Computer Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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