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Items: 1 to 20 of 25

1.

Lipidomic Signature of Progression of Chronic Kidney Disease in the Chronic Renal Insufficiency Cohort.

Afshinnia F, Rajendiran TM, Karnovsky A, Soni T, Wang X, Xie D, Yang W, Shafi T, Weir MR, He J, Brecklin CS, Rhee EP, Schelling JR, Ojo A, Feldman H, Michailidis G, Pennathur S.

Kidney Int Rep. 2016 Nov;1(4):256-268. doi: 10.1016/j.ekir.2016.08.007. Epub 2016 Aug 18.

PMID:
28451650
2.

Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data.

Basu S, Duren W, Evans CR, Burant CF, Michailidis G, Karnovsky A.

Bioinformatics. 2017 May 15;33(10):1545-1553. doi: 10.1093/bioinformatics/btx012.

PMID:
28137712
3.

Metabolomics and Its Application to Acute Lung Diseases.

Stringer KA, McKay RT, Karnovsky A, Quémerais B, Lacy P.

Front Immunol. 2016 Feb 29;7:44. doi: 10.3389/fimmu.2016.00044. eCollection 2016. Review.

4.

ConceptMetab: exploring relationships among metabolite sets to identify links among biomedical concepts.

Cavalcante RG, Patil S, Weymouth TE, Bendinskas KG, Karnovsky A, Sartor MA.

Bioinformatics. 2016 May 15;32(10):1536-43. doi: 10.1093/bioinformatics/btw016. Epub 2016 Jan 21.

PMID:
26794319
5.

Whole Blood Reveals More Metabolic Detail of the Human Metabolome than Serum as Measured by 1H-NMR Spectroscopy: Implications for Sepsis Metabolomics.

Stringer KA, Younger JG, McHugh C, Yeomans L, Finkel MA, Puskarich MA, Jones AE, Trexel J, Karnovsky A.

Shock. 2015 Sep;44(3):200-8. doi: 10.1097/SHK.0000000000000406.

6.

Metabolomics and diabetes: analytical and computational approaches.

Sas KM, Karnovsky A, Michailidis G, Pennathur S.

Diabetes. 2015 Mar;64(3):718-32. doi: 10.2337/db14-0509. Review.

7.

Proteomics analysis of rough endoplasmic reticulum in pancreatic beta cells.

Lee JS, Wu Y, Schnepp P, Fang J, Zhang X, Karnovsky A, Woods J, Stemmer PM, Liu M, Zhang K, Chen X.

Proteomics. 2015 May;15(9):1508-11. doi: 10.1002/pmic.201400345.

8.

Pharmacometabolomics of l-carnitine treatment response phenotypes in patients with septic shock.

Puskarich MA, Finkel MA, Karnovsky A, Jones AE, Trexel J, Harris BN, Stringer KA.

Ann Am Thorac Soc. 2015 Jan;12(1):46-56. doi: 10.1513/AnnalsATS.201409-415OC.

9.

MetDisease--connecting metabolites to diseases via literature.

Duren W, Weymouth T, Hull T, Omenn GS, Athey B, Burant C, Karnovsky A.

Bioinformatics. 2014 Aug 1;30(15):2239-41. doi: 10.1093/bioinformatics/btu179. Epub 2014 Apr 8.

10.

Epithelial-mesenchymal transition-associated secretory phenotype predicts survival in lung cancer patients.

Reka AK, Chen G, Jones RC, Amunugama R, Kim S, Karnovsky A, Standiford TJ, Beer DG, Omenn GS, Keshamouni VG.

Carcinogenesis. 2014 Jun;35(6):1292-300. doi: 10.1093/carcin/bgu041. Epub 2014 Feb 7.

11.

Signal intensities derived from different NMR probes and parameters contribute to variations in quantification of metabolites.

Lacy P, McKay RT, Finkel M, Karnovsky A, Woehler S, Lewis MJ, Chang D, Stringer KA.

PLoS One. 2014 Jan 21;9(1):e85732. doi: 10.1371/journal.pone.0085732. eCollection 2014. Erratum in: PLoS One. 2014;9(7):e102929.

12.

Untargeted LC-MS metabolomics of bronchoalveolar lavage fluid differentiates acute respiratory distress syndrome from health.

Evans CR, Karnovsky A, Kovach MA, Standiford TJ, Burant CF, Stringer KA.

J Proteome Res. 2014 Feb 7;13(2):640-9. doi: 10.1021/pr4007624. Epub 2013 Dec 9.

13.

LRpath analysis reveals common pathways dysregulated via DNA methylation across cancer types.

Kim JH, Karnovsky A, Mahavisno V, Weymouth T, Pande M, Dolinoy DC, Rozek LS, Sartor MA.

BMC Genomics. 2012 Oct 4;13:526. doi: 10.1186/1471-2164-13-526.

14.

Convergence of genetic influences in comorbidity.

McEachin RC, Sannareddy KS, Cavalcoli JD, Karnovsky A, Vink JM, Sartor MA.

BMC Bioinformatics. 2012 Mar 13;13 Suppl 2:S8. doi: 10.1186/1471-2105-13-S2-S8.

15.

Metab2MeSH: annotating compounds with medical subject headings.

Sartor MA, Ade A, Wright Z, States D, Omenn GS, Athey B, Karnovsky A.

Bioinformatics. 2012 May 15;28(10):1408-10. doi: 10.1093/bioinformatics/bts156. Epub 2012 Apr 6.

16.

Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data.

Karnovsky A, Weymouth T, Hull T, Tarcea VG, Scardoni G, Laudanna C, Sartor MA, Stringer KA, Jagadish HV, Burant C, Athey B, Omenn GS.

Bioinformatics. 2012 Feb 1;28(3):373-80. doi: 10.1093/bioinformatics/btr661. Epub 2011 Nov 30.

17.

Molecular characterization of the endoplasmic reticulum: insights from proteomic studies.

Chen X, Karnovsky A, Sans MD, Andrews PC, Williams JA.

Proteomics. 2010 Nov;10(22):4040-52. doi: 10.1002/pmic.201000234. Epub 2010 Nov 2. Review.

18.

Metabolic consequences of sepsis-induced acute lung injury revealed by plasma ¹H-nuclear magnetic resonance quantitative metabolomics and computational analysis.

Stringer KA, Serkova NJ, Karnovsky A, Guire K, Paine R 3rd, Standiford TJ.

Am J Physiol Lung Cell Mol Physiol. 2011 Jan;300(1):L4-L11. doi: 10.1152/ajplung.00231.2010. Epub 2010 Oct 1.

19.

Metscape: a Cytoscape plug-in for visualizing and interpreting metabolomic data in the context of human metabolic networks.

Gao J, Tarcea VG, Karnovsky A, Mirel BR, Weymouth TE, Beecher CW, Cavalcoli JD, Athey BD, Omenn GS, Burant CF, Jagadish HV.

Bioinformatics. 2010 Apr 1;26(7):971-3. doi: 10.1093/bioinformatics/btq048. Epub 2010 Feb 7.

20.

ConceptGen: a gene set enrichment and gene set relation mapping tool.

Sartor MA, Mahavisno V, Keshamouni VG, Cavalcoli J, Wright Z, Karnovsky A, Kuick R, Jagadish HV, Mirel B, Weymouth T, Athey B, Omenn GS.

Bioinformatics. 2010 Feb 15;26(4):456-63. doi: 10.1093/bioinformatics/btp683. Epub 2009 Dec 9.

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