180 related articles for article (PubMed ID: 27294886)
1. Learning mixed graphical models with separate sparsity parameters and stability-based model selection.
Sedgewick AJ; Shi I; Donovan RM; Benos PV
BMC Bioinformatics; 2016 Jun; 17 Suppl 5(Suppl 5):175. PubMed ID: 27294886
[TBL] [Abstract][Full Text] [Related]
2. Stable feature selection for clinical prediction: exploiting ICD tree structure using Tree-Lasso.
Kamkar I; Gupta SK; Phung D; Venkatesh S
J Biomed Inform; 2015 Feb; 53():277-90. PubMed ID: 25500636
[TBL] [Abstract][Full Text] [Related]
3. Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data.
Becker N; Toedt G; Lichter P; Benner A
BMC Bioinformatics; 2011 May; 12():138. PubMed ID: 21554689
[TBL] [Abstract][Full Text] [Related]
4. On Penalty Parameter Selection for Estimating Network Models.
Wysocki AC; Rhemtulla M
Multivariate Behav Res; 2021; 56(2):288-302. PubMed ID: 31672065
[TBL] [Abstract][Full Text] [Related]
5. Graphical modeling of binary data using the LASSO: a simulation study.
Strobl R; Grill E; Mansmann U
BMC Med Res Methodol; 2012 Feb; 12():16. PubMed ID: 22353192
[TBL] [Abstract][Full Text] [Related]
6. Smooth Bayesian network model for the prediction of future high-cost patients with COPD.
Lin S; Zhang Q; Chen F; Luo L; Chen L; Zhang W
Int J Med Inform; 2019 Jun; 126():147-155. PubMed ID: 31029256
[TBL] [Abstract][Full Text] [Related]
7. StabJGL: a stability approach to sparsity and similarity selection in multiple-network reconstruction.
Lingjærde C; Richardson S
Bioinform Adv; 2023; 3(1):vbad185. PubMed ID: 38152341
[TBL] [Abstract][Full Text] [Related]
8. [Standard technical specifications for methacholine chloride (Methacholine) bronchial challenge test (2023)].
; ;
Zhonghua Jie He He Hu Xi Za Zhi; 2024 Feb; 47(2):101-119. PubMed ID: 38309959
[TBL] [Abstract][Full Text] [Related]
9. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
[TBL] [Abstract][Full Text] [Related]
10. Mixed graphical models for integrative causal analysis with application to chronic lung disease diagnosis and prognosis.
Sedgewick AJ; Buschur K; Shi I; Ramsey JD; Raghu VK; Manatakis DV; Zhang Y; Bon J; Chandra D; Karoleski C; Sciurba FC; Spirtes P; Glymour C; Benos PV
Bioinformatics; 2019 Apr; 35(7):1204-1212. PubMed ID: 30192904
[TBL] [Abstract][Full Text] [Related]
11. Gene selection in cancer classification using sparse logistic regression with Bayesian regularization.
Cawley GC; Talbot NL
Bioinformatics; 2006 Oct; 22(19):2348-55. PubMed ID: 16844704
[TBL] [Abstract][Full Text] [Related]
12. Improved Sparse Multi-Class SVM and Its Application for Gene Selection in Cancer Classification.
Huang L; Zhang HH; Zeng ZB; Bushel PR
Cancer Inform; 2013; 12():143-53. PubMed ID: 23966761
[TBL] [Abstract][Full Text] [Related]
13. Bayesian nonlinear model selection for gene regulatory networks.
Ni Y; Stingo FC; Baladandayuthapani V
Biometrics; 2015 Sep; 71(3):585-95. PubMed ID: 25854759
[TBL] [Abstract][Full Text] [Related]
14. Bayesian variable selection with graphical structure learning: Applications in integrative genomics.
Kundu S; Cheng Y; Shin M; Manyam G; Mallick BK; Baladandayuthapani V
PLoS One; 2018; 13(7):e0195070. PubMed ID: 30059495
[TBL] [Abstract][Full Text] [Related]
15. Relevance Vector Machines: Sparse Classification Methods for QSAR.
Burden FR; Winkler DA
J Chem Inf Model; 2015 Aug; 55(8):1529-34. PubMed ID: 26158341
[TBL] [Abstract][Full Text] [Related]
16. Integrative Learning of Structured High-Dimensional Data from Multiple Datasets.
Chang C; Dai Z; Oh J; Long Q
Stat Anal Data Min; 2023 Apr; 16(2):120-134. PubMed ID: 37213790
[TBL] [Abstract][Full Text] [Related]
17. Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models.
Liu H; Roeder K; Wasserman L
Adv Neural Inf Process Syst; 2010 Dec; 24(2):1432-1440. PubMed ID: 25152607
[TBL] [Abstract][Full Text] [Related]
18. The relevance sample-feature machine: a sparse Bayesian learning approach to joint feature-sample selection.
Mohsenzadeh Y; Sheikhzadeh H; Reza AM; Bathaee N; Kalayeh MM
IEEE Trans Cybern; 2013 Dec; 43(6):2241-54. PubMed ID: 23782842
[TBL] [Abstract][Full Text] [Related]
19. A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data.
Bhadra S; Bhattacharyya C; Chandra NR; Mian IS
Algorithms Mol Biol; 2009 Feb; 4():5. PubMed ID: 19239685
[TBL] [Abstract][Full Text] [Related]
20. Comparing estimation methods for psychometric networks with ordinal data.
Johal SK; Rhemtulla M
Psychol Methods; 2023 Dec; 28(6):1251-1272. PubMed ID: 34928677
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]