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DC Field | Value | Language |
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dc.contributor.author | Yu, K | - |
dc.date.accessioned | 2019-08-08T11:32:51Z | - |
dc.date.available | 2019-08-08T11:32:51Z | - |
dc.date.issued | 2018-04-23 | - |
dc.identifier.citation | IEEE/ACM Transactions on Computational Biology and Bioinformatics | en_US |
dc.identifier.issn | 1545-5963 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/18929 | - |
dc.description | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.description.sponsorship | National Natural Science Foundation of China; International Technology Collaboration Research Program of China | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.rights | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.subject | Breast cancer | en_US |
dc.subject | Differentially expressed genes | en_US |
dc.subject | Logistic regression-random forest | en_US |
dc.subject | Bonferroni test | en_US |
dc.subject | Gene interaction networks | en_US |
dc.title | An effective mixed-model for screening differentially expressed genes of breast cancer based on LR-RF | en_US |
dc.type | Article | en_US |
dc.relation.isPartOf | IEEE/ACM Transactions on Computational Biology and Bioinformatics | - |
pubs.publication-status | Accepted | - |
Appears in Collections: | Dept of Mathematics Research Papers |
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FullText.pdf | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | 421.38 kB | Adobe PDF | View/Open |
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