187 related articles for article (PubMed ID: 31350445)
1. A Statistical Test for Differential Network Analysis Based on Inference of Gaussian Graphical Model.
He H; Cao S; Zhang JG; Shen H; Wang YP; Deng HW
Sci Rep; 2019 Jul; 9(1):10863. PubMed ID: 31350445
[TBL] [Abstract][Full Text] [Related]
2. SILGGM: An extensive R package for efficient statistical inference in large-scale gene networks.
Zhang R; Ren Z; Chen W
PLoS Comput Biol; 2018 Aug; 14(8):e1006369. PubMed ID: 30102702
[TBL] [Abstract][Full Text] [Related]
3. FastGGM: An Efficient Algorithm for the Inference of Gaussian Graphical Model in Biological Networks.
Wang T; Ren Z; Ding Y; Fang Z; Sun Z; MacDonald ML; Sweet RA; Wang J; Chen W
PLoS Comput Biol; 2016 Feb; 12(2):e1004755. PubMed ID: 26872036
[TBL] [Abstract][Full Text] [Related]
4. Testing Differential Gene Networks under Nonparanormal Graphical Models with False Discovery Rate Control.
Zhang Q
Genes (Basel); 2020 Feb; 11(2):. PubMed ID: 32033447
[TBL] [Abstract][Full Text] [Related]
5. A new insight into underlying disease mechanism through semi-parametric latent differential network model.
He Y; Ji J; Xie L; Zhang X; Xue F
BMC Bioinformatics; 2018 Dec; 19(Suppl 17):493. PubMed ID: 30591011
[TBL] [Abstract][Full Text] [Related]
6. Information-incorporated Gaussian graphical model for gene expression data.
Yi H; Zhang Q; Lin C; Ma S
Biometrics; 2022 Jun; 78(2):512-523. PubMed ID: 33527365
[TBL] [Abstract][Full Text] [Related]
7. Predictions of the dysregulated competing endogenous RNA signature involved in the progression of human lung adenocarcinoma.
Yang D; He Y; Wu B; Liu R; Wang N; Wang T; Luo Y; Li Y; Liu Y
Cancer Biomark; 2020; 29(3):399-416. PubMed ID: 32741804
[TBL] [Abstract][Full Text] [Related]
8. Comparative analysis of false discovery rate methods in constructing metabolic association networks.
Koo I; Yao S; Zhang X; Kim S
J Bioinform Comput Biol; 2014 Aug; 12(4):1450018. PubMed ID: 25152043
[TBL] [Abstract][Full Text] [Related]
9. Incorporating prior information into differential network analysis using non-paranormal graphical models.
Zhang XF; Ou-Yang L; Yan H
Bioinformatics; 2017 Aug; 33(16):2436-2445. PubMed ID: 28407042
[TBL] [Abstract][Full Text] [Related]
10. A Multiattribute Gaussian Graphical Model for Inferring Multiscale Regulatory Networks: An Application in Breast Cancer.
Chiquet J; Rigaill G; Sundqvist M
Methods Mol Biol; 2019; 1883():143-160. PubMed ID: 30547399
[TBL] [Abstract][Full Text] [Related]
11. An Integrated Approach of Learning Genetic Networks From Genome-Wide Gene Expression Data Using Gaussian Graphical Model and Monte Carlo Method.
Zhao H; Datta S; Duan ZH
Bioinform Biol Insights; 2023; 17():11779322231152972. PubMed ID: 36865982
[TBL] [Abstract][Full Text] [Related]
12. Identification of target gene and prognostic evaluation for lung adenocarcinoma using gene expression meta-analysis, network analysis and neural network algorithms.
Selvaraj G; Kaliamurthi S; Kaushik AC; Khan A; Wei YK; Cho WC; Gu K; Wei DQ
J Biomed Inform; 2018 Oct; 86():120-134. PubMed ID: 30195659
[TBL] [Abstract][Full Text] [Related]
13. Incorporating prior biological knowledge for network-based differential gene expression analysis using differentially weighted graphical LASSO.
Zuo Y; Cui Y; Yu G; Li R; Ressom HW
BMC Bioinformatics; 2017 Feb; 18(1):99. PubMed ID: 28187708
[TBL] [Abstract][Full Text] [Related]
14. MICRAT: a novel algorithm for inferring gene regulatory networks using time series gene expression data.
Yang B; Xu Y; Maxwell A; Koh W; Gong P; Zhang C
BMC Syst Biol; 2018 Dec; 12(Suppl 7):115. PubMed ID: 30547796
[TBL] [Abstract][Full Text] [Related]
15. Efficient proximal gradient algorithm for inference of differential gene networks.
Wang C; Gao F; Giannakis GB; D'Urso G; Cai X
BMC Bioinformatics; 2019 May; 20(1):224. PubMed ID: 31046666
[TBL] [Abstract][Full Text] [Related]
16. Biological network inference using low order partial correlation.
Zuo Y; Yu G; Tadesse MG; Ressom HW
Methods; 2014 Oct; 69(3):266-73. PubMed ID: 25003577
[TBL] [Abstract][Full Text] [Related]
17. Weighted lasso in graphical Gaussian modeling for large gene network estimation based on microarray data.
Shimamura T; Imoto S; Yamaguchi R; Miyano S
Genome Inform; 2007; 19():142-53. PubMed ID: 18546512
[TBL] [Abstract][Full Text] [Related]
18. An integrated approach to infer dynamic protein-gene interactions - A case study of the human P53 protein.
Wang J; Wu Q; Hu XT; Tian T
Methods; 2016 Nov; 110():3-13. PubMed ID: 27514497
[TBL] [Abstract][Full Text] [Related]
19. A boosting approach to structure learning of graphs with and without prior knowledge.
Anjum S; Doucet A; Holmes CC
Bioinformatics; 2009 Nov; 25(22):2929-36. PubMed ID: 19696047
[TBL] [Abstract][Full Text] [Related]
20. Node-based learning of differential networks from multi-platform gene expression data.
Ou-Yang L; Zhang XF; Wu M; Li XL
Methods; 2017 Oct; 129():41-49. PubMed ID: 28579401
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]