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Items: 1 to 20 of 81

1.

Feasibility of using Clinical Element Models (CEM) to standardize phenotype variables in the database of genotypes and phenotypes (dbGaP).

Lin KW, Tharp M, Conway M, Hsieh A, Ross M, Kim J, Kim HE.

PLoS One. 2013 Sep 18;8(9):e76384. doi: 10.1371/journal.pone.0076384. eCollection 2013.

2.

Standardizing Phenotype Variables in the Database of Genotypes and phenotypes (dbGaP) based on Information Models.

Lin KW, Hsieh A, Farzaneh S, Doan S, Kim H.

AMIA Jt Summits Transl Sci Proc. 2013 Mar 18;2013:110. eCollection 2013.

PMID:
24303316
3.

PhenDisco: phenotype discovery system for the database of genotypes and phenotypes.

Doan S, Lin KW, Conway M, Ohno-Machado L, Hsieh A, Feupe SF, Garland A, Ross MK, Jiang X, Farzaneh S, Walker R, Alipanah N, Zhang J, Xu H, Kim HE.

J Am Med Inform Assoc. 2014 Jan-Feb;21(1):31-6. doi: 10.1136/amiajnl-2013-001882. Epub 2013 Aug 29.

4.

Using PhenX measures to identify opportunities for cross-study analysis.

Pan H, Tryka KA, Vreeman DJ, Huggins W, Phillips MJ, Mehta JP, Phillips JH, McDonald CJ, Junkins HA, Ramos EM, Hamilton CM.

Hum Mutat. 2012 May;33(5):849-57. doi: 10.1002/humu.22074. Epub 2012 Apr 3.

5.

NCBI's Database of Genotypes and Phenotypes: dbGaP.

Tryka KA, Hao L, Sturcke A, Jin Y, Wang ZY, Ziyabari L, Lee M, Popova N, Sharopova N, Kimura M, Feolo M.

Nucleic Acids Res. 2014 Jan;42(Database issue):D975-9. doi: 10.1093/nar/gkt1211. Epub 2013 Dec 1.

6.

The NCBI dbGaP database of genotypes and phenotypes.

Mailman MD, Feolo M, Jin Y, Kimura M, Tryka K, Bagoutdinov R, Hao L, Kiang A, Paschall J, Phan L, Popova N, Pretel S, Ziyabari L, Lee M, Shao Y, Wang ZY, Sirotkin K, Ward M, Kholodov M, Zbicz K, Beck J, Kimelman M, Shevelev S, Preuss D, Yaschenko E, Graeff A, Ostell J, Sherry ST.

Nat Genet. 2007 Oct;39(10):1181-6.

7.

Phenotype Information Retrieval for Existing GWAS Studies.

Alipanah N, Lin KW, Venkatesh V, Farzaneh S, Kim HE.

AMIA Jt Summits Transl Sci Proc. 2013 Mar 18;2013:4-8. eCollection 2013.

8.

Ethical aspects of participation in the database of genotypes and phenotypes of the National Center for Biotechnology Information: the Cancer and Leukemia Group B Experience.

Peppercorn J, Shapira I, Deshields T, Kroetz D, Friedman P, Spears P, Collyar DE, Shulman LN, Dressler L, Bertagnolli MM.

Cancer. 2012 Oct 15;118(20):5060-8. doi: 10.1002/cncr.27515. Epub 2012 Mar 13.

9.

Prediction of susceptibility to major depression by a model of interactions of multiple functional genetic variants and environmental factors.

Wong ML, Dong C, Andreev V, Arcos-Burgos M, Licinio J.

Mol Psychiatry. 2012 Jun;17(6):624-33. doi: 10.1038/mp.2012.13. Epub 2012 Mar 27.

10.

Text Categorization of Heart, Lung, and Blood Studies in the Database of Genotypes and Phenotypes (dbGaP) Utilizing n-grams and Metadata Features.

Ross MK, Lin KW, Truong K, Kumar A, Conway M.

Biomed Inform Insights. 2013 Jul 22;6:35-45. doi: 10.4137/BII.S11987. Print 2013.

11.

Using the PhenX Toolkit to Add Standard Measures to a Study.

Hendershot T, Pan H, Haines J, Harlan WR, Junkins HA, Ramos EM, Hamilton CM.

Curr Protoc Hum Genet. 2011 Oct;Chapter 1:Unit1.21. doi: 10.1002/0471142905.hg0121s71.

PMID:
21975939
13.

The Gene, Environment Association Studies consortium (GENEVA): maximizing the knowledge obtained from GWAS by collaboration across studies of multiple conditions.

Cornelis MC, Agrawal A, Cole JW, Hansel NN, Barnes KC, Beaty TH, Bennett SN, Bierut LJ, Boerwinkle E, Doheny KF, Feenstra B, Feingold E, Fornage M, Haiman CA, Harris EL, Hayes MG, Heit JA, Hu FB, Kang JH, Laurie CC, Ling H, Manolio TA, Marazita ML, Mathias RA, Mirel DB, Paschall J, Pasquale LR, Pugh EW, Rice JP, Udren J, van Dam RM, Wang X, Wiggs JL, Williams K, Yu K; GENEVA Consortium..

Genet Epidemiol. 2010 May;34(4):364-72. doi: 10.1002/gepi.20492.

14.

Practical barriers and ethical challenges in genetic data sharing.

Simpson CL, Goldenberg AJ, Culverhouse R, Daley D, Igo RP, Jarvik GP, Mandal DM, Mascalzoni D, Montgomery CG, Pierce B, Plaetke R, Shete S, Goddard KA, Stein CM.

Int J Environ Res Public Health. 2014 Aug 15;11(8):8383-98. doi: 10.3390/ijerph110808383.

15.

The use of phenome-wide association studies (PheWAS) for exploration of novel genotype-phenotype relationships and pleiotropy discovery.

Pendergrass SA, Brown-Gentry K, Dudek SM, Torstenson ES, Ambite JL, Avery CL, Buyske S, Cai C, Fesinmeyer MD, Haiman C, Heiss G, Hindorff LA, Hsu CN, Jackson RD, Kooperberg C, Le Marchand L, Lin Y, Matise TC, Moreland L, Monroe K, Reiner AP, Wallace R, Wilkens LR, Crawford DC, Ritchie MD.

Genet Epidemiol. 2011 Jul;35(5):410-22. doi: 10.1002/gepi.20589. Epub 2011 May 18.

16.

Cancer GAMAdb: database of cancer genetic associations from meta-analyses and genome-wide association studies.

Schully SD, Yu W, McCallum V, Benedicto CB, Dong LM, Wulf A, Clyne M, Khoury MJ.

Eur J Hum Genet. 2011 Aug;19(8):928-30. doi: 10.1038/ejhg.2011.53. Epub 2011 Apr 13.

17.

dbGaP data access requests: a call for greater transparency.

Walker L, Starks H, West KM, Fullerton SM.

Sci Transl Med. 2011 Dec 14;3(113):113cm34. doi: 10.1126/scitranslmed.3002788.

18.

Including additional controls from public databases improves the power of a genome-wide association study.

Mukherjee S, Simon J, Bayuga S, Ludwig E, Yoo S, Orlow I, Viale A, Offit K, Kurtz RC, Olson SH, Klein RJ.

Hum Hered. 2011;72(1):21-34. doi: 10.1159/000330149. Epub 2011 Aug 17.

19.

Mind the dbGAP: the application of data mining to identify biological mechanisms.

Wooten EC, Huggins GS.

Mol Interv. 2011 Apr;11(2):95-102. doi: 10.1124/mi.11.2.6. No abstract available.

20.

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.

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