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Items: 1 to 20 of 95


GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures.

Urbanowicz RJ, Kiralis J, Sinnott-Armstrong NA, Heberling T, Fisher JM, Moore JH.

BioData Min. 2012 Oct 1;5(1):16. doi: 10.1186/1756-0381-5-16.


A classification and characterization of two-locus, pure, strict, epistatic models for simulation and detection.

Urbanowicz RJ, Granizo-Mackenzie AL, Kiralis J, Moore JH.

BioData Min. 2014 Jun 9;7:8. doi: 10.1186/1756-0381-7-8.


Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection.

Urbanowicz RJ, Kiralis J, Fisher JM, Moore JH.

BioData Min. 2012 Sep 26;5(1):15. doi: 10.1186/1756-0381-5-15.


Detecting purely epistatic multi-locus interactions by an omnibus permutation test on ensembles of two-locus analyses.

Wongseree W, Assawamakin A, Piroonratana T, Sinsomros S, Limwongse C, Chaiyaratana N.

BMC Bioinformatics. 2009 Sep 17;10:294. doi: 10.1186/1471-2105-10-294.


Evaluating the ability of tree-based methods and logistic regression for the detection of SNP-SNP interaction.

García-Magariños M, López-de-Ullibarri I, Cao R, Salas A.

Ann Hum Genet. 2009 May;73(Pt 3):360-9. doi: 10.1111/j.1469-1809.2009.00511.x.


Mining pure, strict epistatic interactions from high-dimensional datasets: ameliorating the curse of dimensionality.

Jiang X, Neapolitan RE.

PLoS One. 2012;7(10):e46771. doi: 10.1371/journal.pone.0046771.


A method for detecting epistasis in genome-wide studies using case-control multi-locus association analysis.

Gayán J, González-Pérez A, Bermudo F, Sáez ME, Royo JL, Quintas A, Galan JJ, Morón FJ, Ramirez-Lorca R, Real LM, Ruiz A.

BMC Genomics. 2008 Jul 31;9:360. doi: 10.1186/1471-2164-9-360.


Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering.

Guo X, Meng Y, Yu N, Pan Y.

BMC Bioinformatics. 2014 Apr 10;15:102. doi: 10.1186/1471-2105-15-102.


A novel survival multifactor dimensionality reduction method for detecting gene-gene interactions with application to bladder cancer prognosis.

Gui J, Moore JH, Kelsey KT, Marsit CJ, Karagas MR, Andrew AS.

Hum Genet. 2011 Jan;129(1):101-10. doi: 10.1007/s00439-010-0905-5.


A random forest approach to the detection of epistatic interactions in case-control studies.

Jiang R, Tang W, Wu X, Fu W.

BMC Bioinformatics. 2009 Jan 30;10 Suppl 1:S65. doi: 10.1186/1471-2105-10-S1-S65.


An omnibus permutation test on ensembles of two-locus analyses can detect pure epistasis and genetic heterogeneity in genome-wide association studies.

Setsirichok D, Tienboon P, Jaroonruang N, Kittichaijaroen S, Wongseree W, Piroonratana T, Usavanarong T, Limwongse C, Aporntewan C, Phadoongsidhi M, Chaiyaratana N.

Springerplus. 2013 May 19;2:230. doi: 10.1186/2193-1801-2-230.


GWIS--model-free, fast and exhaustive search for epistatic interactions in case-control GWAS.

Goudey B, Rawlinson D, Wang Q, Shi F, Ferra H, Campbell RM, Stern L, Inouye MT, Ong CS, Kowalczyk A.

BMC Genomics. 2013;14 Suppl 3:S10. doi: 10.1186/1471-2164-14-S3-S10.


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. doi: 10.1016/j.compbiolchem.2014.01.005.


Epi2Loc: an R package to investigate two-locus epistatic models.

Walters RK, Laurin C, Lubke GH.

Twin Res Hum Genet. 2014 Aug;17(4):272-8. doi: 10.1017/thg.2014.38.


Alternative methods for H1 simulations in genome-wide association studies.

Perduca V, Sinoquet C, Mourad R, Nuel G.

Hum Hered. 2012;73(2):95-104. doi: 10.1159/000336194.


Enabling personal genomics with an explicit test of epistasis.

Greene CS, Himmelstein DS, Nelson HH, Kelsey KT, Williams SM, Andrew AS, Karagas MR, Moore JH.

Pac Symp Biocomput. 2010:327-36.


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:S14. doi: 10.1186/1752-0509-6-S3-S14.

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