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Items: 1 to 20 of 122

1.

Integrated approaches to functionally characterize novel factors in lipoprotein metabolism.

Runz H.

Curr Opin Lipidol. 2012 Apr;23(2):104-10. doi: 10.1097/MOL.0b013e328350fc3d. Review.

PMID:
22327609
2.

Functional genomics- and network-driven systems biology approaches for pharmacogenomics and toxicogenomics.

Yang X, Zhang B, Zhu J.

Curr Drug Metab. 2012 Sep 1;13(7):952-67. Review.

PMID:
22591344
3.

Convergent functional genomics of genome-wide association data for bipolar disorder: comprehensive identification of candidate genes, pathways and mechanisms.

Le-Niculescu H, Patel SD, Bhat M, Kuczenski R, Faraone SV, Tsuang MT, McMahon FJ, Schork NJ, Nurnberger JI Jr, Niculescu AB 3rd.

Am J Med Genet B Neuropsychiatr Genet. 2009 Mar 5;150B(2):155-81. doi: 10.1002/ajmg.b.30887.

PMID:
19025758
4.

Network-based analysis of genome wide association data provides novel candidate genes for lipid and lipoprotein traits.

Sharma A, Gulbahce N, Pevzner SJ, Menche J, Ladenvall C, Folkersen L, Eriksson P, Orho-Melander M, Barabási AL.

Mol Cell Proteomics. 2013 Nov;12(11):3398-408. doi: 10.1074/mcp.M112.024851. Epub 2013 Jul 23.

5.

Approaches to lipid metabolism gene identification and characterization in the postgenomic era.

Reue K, Vergnes L.

J Lipid Res. 2006 Sep;47(9):1891-907. Epub 2006 Jul 11. Review.

6.

Where are we in genomics?

Hocquette JF.

J Physiol Pharmacol. 2005 Jun;56 Suppl 3:37-70. Review.

7.

Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease.

Talwar P, Silla Y, Grover S, Gupta M, Agarwal R, Kushwaha S, Kukreti R.

BMC Genomics. 2014 Mar 15;15:199. doi: 10.1186/1471-2164-15-199.

8.

RNAi-based functional profiling of loci from blood lipid genome-wide association studies identifies genes with cholesterol-regulatory function.

Blattmann P, Schuberth C, Pepperkok R, Runz H.

PLoS Genet. 2013;9(2):e1003338. doi: 10.1371/journal.pgen.1003338. Epub 2013 Feb 28.

9.

The tribbles gene family and lipoprotein metabolism.

Angyal A, Kiss-Toth E.

Curr Opin Lipidol. 2012 Apr;23(2):122-6. doi: 10.1097/MOL.0b013e3283508c3b. Review.

PMID:
22274752
10.

Rationale and study design of the CardioGene Study: genomics of in-stent restenosis.

Ganesh SK, Skelding KA, Mehta L, O'Neill K, Joo J, Zheng G, Goldstein J, Simari R, Billings E, Geller NL, Holmes D, O'Neill WW, Nabel EG.

Pharmacogenomics. 2004 Oct;5(7):952-1004.

PMID:
15469413
11.

From genome-wide association studies to functional genomics: new insights into cardiovascular disease.

McPherson R.

Can J Cardiol. 2013 Jan;29(1):23-9. doi: 10.1016/j.cjca.2012.08.017. Epub 2012 Nov 28. Review.

PMID:
23200092
12.

Sortilin as a regulator of lipoprotein metabolism.

Strong A, Rader DJ.

Curr Atheroscler Rep. 2012 Jun;14(3):211-8. doi: 10.1007/s11883-012-0248-x. Review.

PMID:
22538429
13.

Construction of functional linkage gene networks by data integration.

Linghu B, Franzosa EA, Xia Y.

Methods Mol Biol. 2013;939:215-32. doi: 10.1007/978-1-62703-107-3_14.

PMID:
23192549
14.
15.

Genome-wide approaches to finding novel genes for lipid traits: the start of a long road.

Edmondson AC, Rader DJ.

Circ Cardiovasc Genet. 2008 Oct;1(1):3-6. doi: 10.1161/CIRCGENETICS.108.815530. No abstract available.

16.

Genome resources and comparative analysis tools for cardiovascular research.

Liu GE, Adams MD.

Methods Mol Med. 2006;128:101-23.

PMID:
17071992
17.

[Development of antituberculous drugs: current status and future prospects].

Tomioka H, Namba K.

Kekkaku. 2006 Dec;81(12):753-74. Review. Japanese.

PMID:
17240921
18.

Finding genes and variants for lipid levels after genome-wide association analysis.

Willer CJ, Mohlke KL.

Curr Opin Lipidol. 2012 Apr;23(2):98-103. doi: 10.1097/MOL.0b013e328350fad2. Review.

19.

An integrated genomic analysis of gene-function correlation on schizophrenia susceptibility genes.

Chu TT, Liu Y.

J Hum Genet. 2010 May;55(5):285-92. doi: 10.1038/jhg.2010.24. Epub 2010 Mar 26.

PMID:
20339380
20.

Information-based methods for predicting gene function from systematic gene knock-downs.

Weirauch MT, Wong CK, Byrne AB, Stuart JM.

BMC Bioinformatics. 2008 Oct 29;9:463. doi: 10.1186/1471-2105-9-463.

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