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dc.contributor.authorJulkowska, Magdalena
dc.contributor.authorSaade, Stephanie
dc.contributor.authorAgarwal, Gauraw
dc.contributor.authorGao, Ge
dc.contributor.authorPailles, Yveline
dc.contributor.authorMorton, Mitchell
dc.contributor.authorAwlia, Mariam
dc.contributor.authorTester, Mark
dc.date.accessioned2019-06-26T11:38:11Z
dc.date.available2019-06-26T11:38:11Z
dc.date.issued2019-01-13
dc.identifier.urihttp://hdl.handle.net/10754/655714
dc.description.abstractMVApp – Multivariate analysis application for streamlined data analysis and curation Mission statement: Enhanced data processing transparency Interactive and reproducible data curation Quick processing of data with/without selected outliers Increased statistical literacy across the scientific community Efficient data processing pipeline for big and small datasets Community involvement for expanding analyses included in MVApp
dc.relation.urlhttps://epostersonline.com/wep2019/node/17
dc.titleMVApp : Multivariate analysis application for streamlined data analysis and curation
dc.typePoster
dc.conference.dateJANUARY 13 - 17 , 2019
dc.conference.nameWEP Library ePoster competition 2019
dc.conference.locationKAUST
refterms.dateFOA2019-06-26T11:38:11Z


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