Graph Embedding Deep Learning Guides Microbial Biomarkers' Identification (vol 10, 1182, 2019)

被引：1

作者：

Zhu, Qiang ^{[1
,2
]}

Jiang, Xingpeng ^{[2
,3
]}

Zhu, Qing ^{[2
,3
]}

Pan, Min ^{[2
,3
]}

He, Tingting ^{[2
,3
]}

机构：

[1] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China

[2] Cent China Normal Univ, Sch Comp, Wuhan, Peoples R China

[3] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan, Peoples R China

来源：

FRONTIERS IN GENETICS | 2020年 / 11卷

关键词：

graph embedding; deep learning; feature selection; biomarkers; microbiome;

D O I：

10.3389/fgene.2020.00487

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

引用

页数：2

共 4 条

[1] A Survey of Methods for Explaining Black Box Models [J].

Guidotti, Riccardo ;

Monreale, Anna ;

Ruggieri, Salvatore ;

Turin, Franco ;

Giannotti, Fosca ;

Pedreschi, Dino .

ACM COMPUTING SURVEYS, 2019, 51 (05)

[2] A graph-embedded deep feedforward network for disease outcome classification and feature selection using gene expression data [J].

Kong, Yunchuan ;

Yu, Tianwei .

BIOINFORMATICS, 2018, 34 (21) :3727-3737

[3] Illuminating the "black box": a randomization approach for understanding variable contributions in artificial neural networks [J].

Olden, JD ;

Jackson, DA .

ECOLOGICAL MODELLING, 2002, 154 (1-2) :135-150

[4] Graph Embedding Deep Learning Guides Microbial Biomarkers' Identification [J].

Zhu, Qiang ;

Jiang, Xingpeng ;

Zhu, Qing ;

Pan, Min ;

He, Tingting .

FRONTIERS IN GENETICS, 2019, 10

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