Identifying the gene signatures from gene-pathway bipartite network guarantees the robust model performance on predicting the cancer prognosis.
| Publicado en: | BioMed Research International Vol. 2014; pp. 424509 - 424510 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103840210&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103840210 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 2014 vid: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103840210 103840210 2012684494 NLM25126556 PMC4122106 103840210 ppf: 424509 ppct: 1 formats: fmt: @attributes: type: P tig: atl: Identifying the gene signatures from gene-pathway bipartite network guarantees the robust model performance on predicting the cancer prognosis. aug: au: He, Li Wang, Yuelong Yang, Yongning Huang, Liqiu Wen, Zhining affil: Biogas Institute of Ministry of Agriculture, Chengdu 610041, China. sug: subj: Genes Proteins Neoplasms Oligonucleotide Array Sequence Analysis Methods Algorithms Artificial Intelligence Gene Expression Profiling Methods Molecular Structure Human Neoplasms Pathology Prognosis pubtype: Academic Journal doctype: research Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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