189 related articles for article (PubMed ID: 19209715)
1. Biofilter: a knowledge-integration system for the multi-locus analysis of genome-wide association studies.
Bush WS; Dudek SM; Ritchie MD
Pac Symp Biocomput; 2009; ():368-79. PubMed ID: 19209715
[TBL] [Abstract][Full Text] [Related]
2. Finding unique filter sets in PLATO: a precursor to efficient interaction analysis in GWAS data.
Grady BJ; Torstenson E; Dudek SM; Giles J; Sexton D; Ritchie MD
Pac Symp Biocomput; 2010; ():315-26. PubMed ID: 19908384
[TBL] [Abstract][Full Text] [Related]
3. Statistical epistasis networks reduce the computational complexity of searching three-locus genetic models.
Hu T; Andrew AS; Karagas MR; Moore JH
Pac Symp Biocomput; 2013; ():397-408. PubMed ID: 23424144
[TBL] [Abstract][Full Text] [Related]
4. Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit.
Pendergrass SA; Verma SS; Holzinger ER; Moore CB; Wallace J; Dudek SM; Huggins W; Kitchner T; Waudby C; Berg R; McCarty CA; Ritchie MD
Pac Symp Biocomput; 2013; ():147-58. PubMed ID: 23424120
[TBL] [Abstract][Full Text] [Related]
5. Discovering SNP-disease relationships in genome-wide SNP data using an improved harmony search based on SNP locus and genetic inheritance patterns.
Esmaeili F; Narimani Z; Vasighi M
PLoS One; 2023; 18(10):e0292266. PubMed ID: 37831690
[TBL] [Abstract][Full Text] [Related]
6. MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome wide association study.
Wan X; Yang C; Yang Q; Xue H; Tang NL; Yu W
BMC Bioinformatics; 2009 Jan; 10():13. PubMed ID: 19134182
[TBL] [Abstract][Full Text] [Related]
7. KNOWLEDGE DRIVEN BINNING AND PHEWAS ANALYSIS IN MARSHFIELD PERSONALIZED MEDICINE RESEARCH PROJECT USING BIOBIN.
Basile AO; Wallace JR; Peissig P; McCarty CA; Brilliant M; Ritchie MD
Pac Symp Biocomput; 2016; 21():249-60. PubMed ID: 26776191
[TBL] [Abstract][Full Text] [Related]
8. HiSSI: high-order SNP-SNP interactions detection based on efficient significant pattern and differential evolution.
Cao X; Liu J; Guo M; Wang J
BMC Med Genomics; 2019 Dec; 12(Suppl 7):139. PubMed ID: 31888641
[TBL] [Abstract][Full Text] [Related]
9. OPATs: Omnibus P-value association tests.
Chen CW; Yang HC
Brief Bioinform; 2019 Jan; 20(1):1-14. PubMed ID: 28981573
[TBL] [Abstract][Full Text] [Related]
10. Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using biofilter, and gene-environment interactions using the Phenx Toolkit*.
Pendergrass SA; Verma SS; Hall MA; Holzinger ER; Moore CB; Wallace JR; Dudek SM; Huggins W; Kitchner T; Waudby C; Berg R; Mccarty CA; Ritchie MD
Pac Symp Biocomput; 2015; ():495-505. PubMed ID: 25741542
[TBL] [Abstract][Full Text] [Related]
11. Machine learning in genome-wide association studies.
Szymczak S; Biernacka JM; Cordell HJ; González-Recio O; König IR; Zhang H; Sun YV
Genet Epidemiol; 2009; 33 Suppl 1():S51-7. PubMed ID: 19924717
[TBL] [Abstract][Full Text] [Related]
12. FastChi: an efficient algorithm for analyzing gene-gene interactions.
Zhang X; Zou F; Wang W
Pac Symp Biocomput; 2009; ():528-39. PubMed ID: 19209728
[TBL] [Abstract][Full Text] [Related]
13. Bayesian variable and model selection methods for genetic association studies.
Fridley BL
Genet Epidemiol; 2009 Jan; 33(1):27-37. PubMed ID: 18618760
[TBL] [Abstract][Full Text] [Related]
14. Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.
Nguyen TT; Huang J; Wu Q; Nguyen T; Li M
BMC Genomics; 2015; 16 Suppl 2(Suppl 2):S5. PubMed ID: 25708662
[TBL] [Abstract][Full Text] [Related]
15. Leveraging putative enhancer-promoter interactions to investigate two-way epistasis in Type 2 Diabetes GWAS.
Manduchi E; Chesi A; Hall MA; Grant SFA; Moore JH
Pac Symp Biocomput; 2018; 23():548-558. PubMed ID: 29218913
[TBL] [Abstract][Full Text] [Related]
16. PHENOME-WIDE INTERACTION STUDY (PheWIS) IN AIDS CLINICAL TRIALS GROUP DATA (ACTG).
Verma SS; Frase AT; Verma A; Pendergrass SA; Mahony S; Haas DW; Ritchie MD
Pac Symp Biocomput; 2016; 21():57-68. PubMed ID: 26776173
[TBL] [Abstract][Full Text] [Related]
17. Genome-wide genetic interaction analysis of glaucoma using expert knowledge derived from human phenotype networks.
Hu T; Darabos C; Cricco ME; Kong E; Moore JH
Pac Symp Biocomput; 2015; 20():207-18. PubMed ID: 25592582
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Using biological knowledge to uncover the mystery in the search for epistasis in genome-wide association studies.
Ritchie MD
Ann Hum Genet; 2011 Jan; 75(1):172-82. PubMed ID: 21158748
[TBL] [Abstract][Full Text] [Related]
20. An ensemble learning approach jointly modeling main and interaction effects in genetic association studies.
Zhang Z; Zhang S; Wong MY; Wareham NJ; Sha Q
Genet Epidemiol; 2008 May; 32(4):285-300. PubMed ID: 18205210
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
