Please use this identifier to cite or link to this item: http://hdl.handle.net/10263/7367
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dc.contributor.authorDutta, Akash-
dc.date.accessioned2023-07-11T17:13:10Z-
dc.date.available2023-07-11T17:13:10Z-
dc.date.issued2023-06-
dc.identifier.citation32p.en_US
dc.identifier.urihttp://hdl.handle.net/10263/7367-
dc.descriptionDissertation under the supervision of Prof. Shubhra Sankar Rayen_US
dc.description.abstractMicroRNAs (miRNAs) refer to tiny RNA molecules that have a crucial part in regulat- ing drug sensitivity and resistance in cancer. Identifying these miRNAs can significantly enhance the effectiveness of cancer treatment. In this study, a computational method is developed to identify drug resistant miRNAs. Additionally, a comprehensive review of studies focused on identifying those miRNAs is presented. The developed method intro- duces a scoring system based on expressions of miRNAs in control and resistant groups and involves integration of absolute distance, fold change, and Pearson correlation coeffi- cient in a weighted framework to reduce the average ranking of miRNAs. In the process, the power of the fold change is also varied. Arranging the miRNAs in a descending order based on the score helps in selecting the top ranked miRNAs which helps in classification of the patients. This score offers an effective strategy for identifying miRNAs linked to drug resistance in cancer. Its application may provide valuable insights into potential therapeutic targets, thereby improving the outcomes of cancer treatment.en_US
dc.language.isoenen_US
dc.publisherIndian Statistical Institute, Kolkataen_US
dc.relation.ispartofseriesDissertation;2023-1-
dc.subjectDrug Resistanen_US
dc.subjectCanceren_US
dc.subjectmiRNAen_US
dc.titleIdentifying Drug Resistant miRNAs In Canceren_US
dc.typeOtheren_US
Appears in Collections:Dissertations - M Tech (CS)

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