Please use this identifier to cite or link to this item: http://repository.iiitd.edu.in/xmlui/handle/123456789/2076
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dc.contributor.authorVerma, Shriya-
dc.contributor.authorSethi, Tavpritesh (Advisor)-
dc.date.accessioned2026-09-02T09:41:12Z-
dc.date.available2026-09-02T09:41:12Z-
dc.date.issued2024-11-27-
dc.identifier.urihttp://repository.iiitd.edu.in/xmlui/handle/123456789/2076-
dc.description.abstractGenerative genomics refers to the field of study focused on developing computational models and algorithms capable of generating synthetic genomic data. This report explores the application of transformer-based architectures for generating synthetic genomic data. The literature review gives an overview of different transformer-based architectures explored through the term. Some challenges faced during implementation and the innovative solutions for them are also included. The potential applications of generative genomics and the scope for future research in the evolving field are also covered in this report.en_US
dc.language.isoen_USen_US
dc.publisherIIIT-Delhien_US
dc.subjectTransformersen_US
dc.subjectGenerative Genomicsen_US
dc.subjectMachine Learningen_US
dc.titleGenerative genomicsen_US
dc.typeOtheren_US
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