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Items: 1 to 20 of 67

1.

Genotype-phenotype mapping in a post-GWAS world.

Nuzhdin SV, Friesen ML, McIntyre LM.

Trends Genet. 2012 Sep;28(9):421-6. doi: 10.1016/j.tig.2012.06.003. Epub 2012 Jul 18.

2.

An integrative bioinformatics framework for genome-scale multiple level network reconstruction of rice.

Liu L, Mei Q, Yu Z, Sun T, Zhang Z, Chen M.

J Integr Bioinform. 2013 Apr 5;10(2):223. doi: 10.2390/biecoll-jib-2013-223.

PMID:
23563093
3.

GWAS analyzer: integrating genotype, phenotype and public annotation data for genome-wide association study analysis.

Fong C, Ko DC, Wasnick M, Radey M, Miller SI, Brittnacher M.

Bioinformatics. 2010 Feb 15;26(4):560-4. doi: 10.1093/bioinformatics/btp714. Epub 2010 Jan 6.

4.

Prioritization of SNPs for genome-wide association studies using an interaction model of genetic variation, gene expression, and trait variation.

Paik H, Kim J, Lee S, Heo HS, Hur CG, Lee D.

Mol Cells. 2012 Apr;33(4):351-61. doi: 10.1007/s10059-012-2264-7. Epub 2012 Mar 28.

5.

From genotype to phenotype: systems biology meets natural variation.

Benfey PN, Mitchell-Olds T.

Science. 2008 Apr 25;320(5875):495-7. doi: 10.1126/science.1153716.

6.

Genotype networks in metabolic reaction spaces.

Samal A, Matias Rodrigues JF, Jost J, Martin OC, Wagner A.

BMC Syst Biol. 2010 Mar 19;4:30. doi: 10.1186/1752-0509-4-30.

7.
8.

Genetic algorithms and their application to in silico evolution of genetic regulatory networks.

Knabe JF, Wegner K, Nehaniv CL, Schilstra MJ.

Methods Mol Biol. 2010;673:297-321. doi: 10.1007/978-1-60761-842-3_19.

PMID:
20835807
9.

The evolutionary developmental biology of tinkering: an introduction to the challenge.

Lieberman DE, Hall BK.

Novartis Found Symp. 2007;284:1-19; discussion 110-5. Review.

PMID:
17710844
10.

Integrating Microarray Data and GRNs.

Koumakis L, Potamias G, Tsiknakis M, Zervakis M, Moustakis V.

Methods Mol Biol. 2016;1375:137-53. doi: 10.1007/7651_2015_252.

PMID:
26134183
11.

phenosim--A software to simulate phenotypes for testing in genome-wide association studies.

Günther T, Gawenda I, Schmid KJ.

BMC Bioinformatics. 2011 Jun 29;12:265. doi: 10.1186/1471-2105-12-265.

12.

Identification of homogeneous genetic architecture of multiple genetically correlated traits by block clustering of genome-wide associations.

Gupta M, Cheung CL, Hsu YH, Demissie S, Cupples LA, Kiel DP, Karasik D.

J Bone Miner Res. 2011 Jun;26(6):1261-71. doi: 10.1002/jbmr.333.

13.

Mechanistic explanations for restricted evolutionary paths that emerge from gene regulatory networks.

Cotterell J, Sharpe J.

PLoS One. 2013 Apr 17;8(4):e61178. doi: 10.1371/journal.pone.0061178. Print 2013.

14.

Integrating pathway analysis and genetics of gene expression for genome-wide association studies.

Zhong H, Yang X, Kaplan LM, Molony C, Schadt EE.

Am J Hum Genet. 2010 Apr 9;86(4):581-91. doi: 10.1016/j.ajhg.2010.02.020. Epub 2010 Mar 25.

15.

Alcohol sensitivity in Drosophila: translational potential of systems genetics.

Morozova TV, Ayroles JF, Jordan KW, Duncan LH, Carbone MA, Lyman RF, Stone EA, Govindaraju DR, Ellison RC, Mackay TF, Anholt RR.

Genetics. 2009 Oct;183(2):733-45, 1SI-12SI. doi: 10.1534/genetics.109.107490. Epub 2009 Aug 3.

16.

Genome-wide association study of alcohol dependence.

Treutlein J, Cichon S, Ridinger M, Wodarz N, Soyka M, Zill P, Maier W, Moessner R, Gaebel W, Dahmen N, Fehr C, Scherbaum N, Steffens M, Ludwig KU, Frank J, Wichmann HE, Schreiber S, Dragano N, Sommer WH, Leonardi-Essmann F, Lourdusamy A, Gebicke-Haerter P, Wienker TF, Sullivan PF, Nöthen MM, Kiefer F, Spanagel R, Mann K, Rietschel M.

Arch Gen Psychiatry. 2009 Jul;66(7):773-84. doi: 10.1001/archgenpsychiatry.2009.83.

17.

Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders.

Andrews T, Meader S, Vulto-van Silfhout A, Taylor A, Steinberg J, Hehir-Kwa J, Pfundt R, de Leeuw N, de Vries BB, Webber C.

PLoS Genet. 2015 Mar 17;11(3):e1005012. doi: 10.1371/journal.pgen.1005012. eCollection 2015 Mar.

18.

Interlinked nonlinear subnetworks underlie the formation of robust cellular patterns in Arabidopsis epidermis: a dynamic spatial model.

Benítez M, Espinosa-Soto C, Padilla-Longoria P, Alvarez-Buylla ER.

BMC Syst Biol. 2008 Nov 17;2:98. doi: 10.1186/1752-0509-2-98.

19.

Genome-wide association mapping identifies the genetic basis of discrete and quantitative variation in sexual weaponry in a wild sheep population.

Johnston SE, McEwan JC, Pickering NK, Kijas JW, Beraldi D, Pilkington JG, Pemberton JM, Slate J.

Mol Ecol. 2011 Jun;20(12):2555-66. doi: 10.1111/j.1365-294X.2011.05076.x. Epub 2011 Mar 29.

PMID:
21651634
20.

Extreme-phenotype genome-wide association study (XP-GWAS): a method for identifying trait-associated variants by sequencing pools of individuals selected from a diversity panel.

Yang J, Jiang H, Yeh CT, Yu J, Jeddeloh JA, Nettleton D, Schnable PS.

Plant J. 2015 Nov;84(3):587-96. doi: 10.1111/tpj.13029.

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