Machine Learning for the Exploitation of High Throughput Omics Data: A Case Study on Identifying Circadian Disruption from Human Blood Transcriptomic Data

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dc.contributor.advisorDr. Emma Laing, supervisor / Dr. H. Lilian Tang, supervisor
dc.contributor.authorNOFE ATEQ MOHAMMEDSAEED ALGANMI
dc.date2019
dc.date.accessioned2022-05-29T10:25:38Z
dc.date.available2022-05-29T10:25:38Z
dc.degree.departmentBIOINFORMATICS
dc.identifier.other40578
dc.identifier.urihttps://drepo.sdl.edu.sa/handle/20.500.14154/45122
dc.publisherSaudi Digital Library
dc.titleMachine Learning for the Exploitation of High Throughput Omics Data: A Case Study on Identifying Circadian Disruption from Human Blood Transcriptomic Data
dc.typeThesis
sdl.thesis.levelDoctoral
sdl.thesis.sourceSACM - United Kingdom

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