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dc.contributor.authorKuznetsova, I.
dc.contributor.authorKarpievitch, Y.
dc.contributor.authorFilipovska, A.
dc.contributor.authorLugmayr, Artur
dc.contributor.authorHolzinger, A.
dc.date.accessioned2017-08-24T02:23:15Z
dc.date.available2017-08-24T02:23:15Z
dc.date.created2017-08-23T07:21:34Z
dc.date.issued2016
dc.identifier.citationKuznetsova, I. and Karpievitch, Y. and Filipovska, A. and Lugmayr, A. and Holzinger, A. 2016. Review of machine learning algorithms in differential expression analysis, pp. 11-24.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/56285
dc.description.abstract

In biological research machine learning algorithms are part of nearly every analytical process. They are used to identify new insights into biological phenomena, interpret data, provide molecular diagnosis for diseases and develop personalized medicine that will enable future treatments of diseases. In this paper we (1) illustrate the importance of machine learning in the analysis of large scale sequencing data, (2) present an illustrative standardized workflow of the analysis process, (3) perform a Differential Expression (DE) analysis of a publicly available RNA sequencing (RNA-Seq) data set to demonstrate the capabilities of various algorithms at each step of the workflow, and (4) show a machine learning solution in improving the computing time, storage requirements, and minimize utilization of computer memory in analyses of RNA-Seq datasets. The source code of the analysis pipeline and associated scripts are presented in the paper appendix to allow replication of experiments.

dc.titleReview of machine learning algorithms in differential expression analysis
dc.typeConference Paper
dcterms.source.volume2016
dcterms.source.startPage11
dcterms.source.endPage24
dcterms.source.titleInternational series on information systems and management in creative eMedia
dcterms.source.seriesInternational series on information systems and management in creative eMedia
dcterms.source.isbn9781510800168
curtin.departmentDepartment of Film and Television
curtin.accessStatusFulltext not available


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