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dc.contributor.authorWang, Yan
dc.contributor.authorDu, Wei
dc.contributor.authorLiang, Yanchun
dc.contributor.authorChen, Xin
dc.contributor.authorZhang, Chi
dc.contributor.authorPang, Wei
dc.contributor.authorXu, Ying
dc.contributor.editorLi, Jinyan
dc.contributor.editorLi, Xue
dc.contributor.editorWang, Shuliang
dc.contributor.editorLi, Jianxin
dc.contributor.editorSheng, Quan Z.
dc.date.accessioned2017-11-14T00:02:19Z
dc.date.available2017-11-14T00:02:19Z
dc.date.issued2016
dc.identifier.citationWang , Y , Du , W , Liang , Y , Chen , X , Zhang , C , Pang , W & Xu , Y 2016 , PUEPro : A Computational Pipeline for Prediction of Urine Excretory Proteins . in J Li , X Li , S Wang , J Li & Q Z Sheng (eds) , Advanced Data Mining and Applications : 2th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12-15, 2016, Proceedings . Lecture Notes in Artificial Intelligence (LNAI) , Springer International Publishing , pp. 714-725 , ADMA 2016 , Gold Coast , Australia , 12-15 December . DOI: 10.1007/978-3-319-49586-6_51en
dc.identifier.citationconferenceen
dc.identifier.isbn978-3-319-49585-9
dc.identifier.isbn978-3-319-49586-6
dc.identifier.otherPURE: 71319337
dc.identifier.otherPURE UUID: 796c0813-d103-4c18-9b72-400b09580e83
dc.identifier.otherScopus: 85000366259
dc.identifier.urihttp://hdl.handle.net/2164/9596
dc.descriptionThis work is supported by the National Natural Science Foundation of China (Grant Nos. 81320108025, 61402194, 61572227), Development Project of Jilin Province of China (20140101180JC) and China Postdoctoral Science Foundation (2014T70291).en
dc.format.extent12en
dc.language.isoeng
dc.publisherSpringer International Publishing
dc.relation.ispartofAdvanced Data Mining and Applicationsen
dc.relation.ispartofseriesLecture Notes in Artificial Intelligence (LNAI)en
dc.rightsThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-49586-6_51en
dc.subjecturine excretory proteinsen
dc.subjectsupport vector machine recursive feature eliminationen
dc.subjectbiomarkers of diseaseen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subject.lccQA75en
dc.titlePUEPro : A Computational Pipeline for Prediction of Urine Excretory Proteinsen
dc.typeConference itemen
dc.contributor.institutionUniversity of Aberdeen, Natural & Computing Sciences, Computing Scienceen
dc.description.versionPostprinten
dc.identifier.doihttp://dx.doi.org/10.1007/978-3-319-49586-6_51
dc.date.embargoedUntil13-11-20


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