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dc.contributor.authorGimenez Devis, Cristobal
dc.date.accessioned2024-08-13T00:00:37Z
dc.date.available2024-08-13T00:00:37Z
dc.date.issued2024-06-03
dc.date.submitted2024-06-03T10:07:01Z
dc.identifierINF399 0 O ORD 2024 VÅR
dc.identifier.urihttps://hdl.handle.net/11250/3145869
dc.description.abstractBreast cancer is a complex, heterogeneous disease with distinct cancer subtypes. When the breast organ develops, it has a large pool of mammary stem cells. These cells have the potential to give rise to the various cell types that constitute the breast, as such, they are at risk for acquiring mutations, which can lead to transformed stem cells, thereby promoting the process of tumorigenesis. Among the breast cancer cells, increasing evidence points to the presence of a rare, small and heterogeneous subpopulation of cancerous cells termed as breast cancer stem cells (BCSCs), which have unlimited renewal capacity and are responsible for repopulating and giving rise to the heterogeneous, overly aggressive tumors. The recent technology of gene expression profiling like RNA-seq has helped some studies try to figure a way of identifying BCSCs, but there is still much work to be done. In this work we will use Machine Learning approach together with RNA-seq techonology in order to try to solve this task.
dc.language.isoeng
dc.publisherThe University of Bergen
dc.rightsCopyright the Author. All rights reserved
dc.subjectMachine Learning
dc.subjectStem cells
dc.subjectBreast cancer
dc.subjectNeural Networks
dc.titleStem cell identification via RNA sequencing in breast cancer.
dc.typeMaster thesis
dc.date.updated2024-06-03T10:07:01Z
dc.rights.holderCopyright the Author. All rights reserved
dc.description.degreeMasteroppgave i informatikk
dc.description.localcodeINF399
dc.description.localcodeMAMN-PROG
dc.description.localcodeMAMN-INF
dc.subject.nus754199
fs.subjectcodeINF399
fs.unitcode12-12-0


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