193 related articles for article (PubMed ID: 21346997)
1. A fast algorithm for learning epistatic genomic relationships.
Jiang X; Neapolitan RE; Barmada MM; Visweswaran S; Cooper GF
AMIA Annu Symp Proc; 2010 Nov; 2010():341-5. PubMed ID: 21346997
[TBL] [Abstract][Full Text] [Related]
2. Genetic studies of complex human diseases: characterizing SNP-disease associations using Bayesian networks.
Han B; Chen XW; Talebizadeh Z; Xu H
BMC Syst Biol; 2012; 6 Suppl 3(Suppl 3):S14. PubMed ID: 23281790
[TBL] [Abstract][Full Text] [Related]
3. Learning genetic epistasis using Bayesian network scoring criteria.
Jiang X; Neapolitan RE; Barmada MM; Visweswaran S
BMC Bioinformatics; 2011 Mar; 12():89. PubMed ID: 21453508
[TBL] [Abstract][Full Text] [Related]
4. LEAP: biomarker inference through learning and evaluating association patterns.
Jiang X; Neapolitan RE
Genet Epidemiol; 2015 Mar; 39(3):173-84. PubMed ID: 25677188
[TBL] [Abstract][Full Text] [Related]
5. Mining pure, strict epistatic interactions from high-dimensional datasets: ameliorating the curse of dimensionality.
Jiang X; Neapolitan RE
PLoS One; 2012; 7(10):e46771. PubMed ID: 23071633
[TBL] [Abstract][Full Text] [Related]
6. Cuckoo search epistasis: a new method for exploring significant genetic interactions.
Aflakparast M; Salimi H; Gerami A; Dubé MP; Visweswaran S; Masoudi-Nejad A
Heredity (Edinb); 2014 Jun; 112(6):666-74. PubMed ID: 24549111
[TBL] [Abstract][Full Text] [Related]
7. GESLM algorithm for detecting causal SNPs in GWAS with multiple phenotypes.
Lyu R; Sun J; Xu D; Jiang Q; Wei C; Zhang Y
Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34323927
[TBL] [Abstract][Full Text] [Related]
8. SMMB: a stochastic Markov blanket framework strategy for epistasis detection in GWAS.
Niel C; Sinoquet C; Dina C; Rocheleau G
Bioinformatics; 2018 Aug; 34(16):2773-2780. PubMed ID: 29547902
[TBL] [Abstract][Full Text] [Related]
9. Discovering causal interactions using Bayesian network scoring and information gain.
Zeng Z; Jiang X; Neapolitan R
BMC Bioinformatics; 2016 May; 17(1):221. PubMed ID: 27230078
[TBL] [Abstract][Full Text] [Related]
10. bNEAT: a Bayesian network method for detecting epistatic interactions in genome-wide association studies.
Han B; Chen XW
BMC Genomics; 2011; 12 Suppl 2(Suppl 2):S9. PubMed ID: 21989368
[TBL] [Abstract][Full Text] [Related]
11. Epi-GTBN: an approach of epistasis mining based on genetic Tabu algorithm and Bayesian network.
Guo Y; Zhong Z; Yang C; Hu J; Jiang Y; Liang Z; Gao H; Liu J
BMC Bioinformatics; 2019 Aug; 20(1):444. PubMed ID: 31455207
[TBL] [Abstract][Full Text] [Related]
12. GEP-EpiSeeker: a gene expression programming-based method for epistatic interaction detection in genome-wide association studies.
Peng YZ; Lin Y; Huang Y; Li Y; Luo G; Liao J
BMC Genomics; 2021 Dec; 22(Suppl 1):910. PubMed ID: 34930147
[TBL] [Abstract][Full Text] [Related]
13. Fast detection of high-order epistatic interactions in genome-wide association studies using information theoretic measure.
Leem S; Jeong HH; Lee J; Wee K; Sohn KA
Comput Biol Chem; 2014 Jun; 50():19-28. PubMed ID: 24581733
[TBL] [Abstract][Full Text] [Related]
14. A comparative analysis of methods for predicting clinical outcomes using high-dimensional genomic datasets.
Jiang X; Cai B; Xue D; Lu X; Cooper GF; Neapolitan RE
J Am Med Inform Assoc; 2014 Oct; 21(e2):e312-9. PubMed ID: 24737607
[TBL] [Abstract][Full Text] [Related]
15. A Bayesian model for detection of high-order interactions among genetic variants in genome-wide association studies.
Wang J; Joshi T; Valliyodan B; Shi H; Liang Y; Nguyen HT; Zhang J; Xu D
BMC Genomics; 2015 Nov; 16():1011. PubMed ID: 26607428
[TBL] [Abstract][Full Text] [Related]
16. EpiMOGA: An Epistasis Detection Method Based on a Multi-Objective Genetic Algorithm.
Chen Y; Xu F; Pian C; Xu M; Kong L; Fang J; Li Z; Zhang L
Genes (Basel); 2021 Jan; 12(2):. PubMed ID: 33525573
[TBL] [Abstract][Full Text] [Related]
17. Multi-Objective Artificial Bee Colony Algorithm Based on Scale-Free Network for Epistasis Detection.
Gu Y; Sun Y; Shang J; Li F; Guan B; Liu JX
Genes (Basel); 2022 May; 13(5):. PubMed ID: 35627256
[TBL] [Abstract][Full Text] [Related]
18. Identifying genetic interactions in genome-wide data using Bayesian networks.
Jiang X; Barmada MM; Visweswaran S
Genet Epidemiol; 2010 Sep; 34(6):575-81. PubMed ID: 20568290
[TBL] [Abstract][Full Text] [Related]
19. Searching Genome-Wide Multi-Locus Associations for Multiple Diseases Based on Bayesian Inference.
Guo X; Zhang J; Cai Z; Du DZ; Pan Y
IEEE/ACM Trans Comput Biol Bioinform; 2017; 14(3):600-610. PubMed ID: 26887006
[TBL] [Abstract][Full Text] [Related]
20. An Approach of Epistasis Detection Using Integer Linear Programming Optimizing Bayesian Network.
Yang X; Yang C; Lei J; Liu J
IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(5):2654-2671. PubMed ID: 34181547
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]