Literature DB >> 12700956

Microarrays: new tools for transplantation research.

Mei-Sze Chua1, Minnie M Sarwal.   

Abstract

The advent of DNA microarray technology has greatly enhanced our potential to understand the molecular basis of human diseases and to aid in more accurate classification, diagnosis and/or prognosis. This powerful, flexible and highly informative technique has been adopted by many biomedical research disciplines. The use of DNA microarrays for gene expression profiling of patients undergoing organ transplantation has diagnostic and therapeutic potential. By generating global views of the gene expression changes in renal graft function post transplantation, DNA microarray technology will provide important information to improve our understanding of the molecular basis of various causes of graft dysfunction, and therefore suggest improved diagnosis, disease classification, and treatment.

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Year:  2003        PMID: 12700956     DOI: 10.1007/s00467-003-1083-7

Source DB:  PubMed          Journal:  Pediatr Nephrol        ISSN: 0931-041X            Impact factor:   3.714


  37 in total

1.  High-fidelity mRNA amplification for gene profiling.

Authors:  E Wang; L D Miller; G A Ohnmacht; E T Liu; F M Marincola
Journal:  Nat Biotechnol       Date:  2000-04       Impact factor: 54.908

2.  Altered patterns of gene expression in response to myocardial infarction.

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Journal:  Circ Res       Date:  2000-05-12       Impact factor: 17.367

Review 3.  Prospective use of DNA microarrays for evaluating renal function and disease.

Authors:  L L Hsiao; R L Stears; R L Hong; S R Gullans
Journal:  Curr Opin Nephrol Hypertens       Date:  2000-05       Impact factor: 2.894

4.  Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations.

Authors:  M L Lee; F C Kuo; G A Whitmore; J Sklar
Journal:  Proc Natl Acad Sci U S A       Date:  2000-08-29       Impact factor: 11.205

5.  Amplified RNA synthesized from limited quantities of heterogeneous cDNA.

Authors:  R N Van Gelder; M E von Zastrow; A Yool; W C Dement; J D Barchas; J H Eberwine
Journal:  Proc Natl Acad Sci U S A       Date:  1990-03       Impact factor: 11.205

6.  Alterations of gene expression during colorectal carcinogenesis revealed by cDNA microarrays after laser-capture microdissection of tumor tissues and normal epithelia.

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Journal:  Cancer Res       Date:  2001-05-01       Impact factor: 12.701

7.  Granulysin expression is a marker for acute rejection and steroid resistance in human renal transplantation.

Authors:  M M Sarwal; A Jani; S Chang; P Huie; Z Wang; O Salvatierra; C Clayberger; R Sibley; A M Krensky; M Pavlakis
Journal:  Hum Immunol       Date:  2001-01       Impact factor: 2.850

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Authors:  M Schena; D Shalon; R W Davis; P O Brown
Journal:  Science       Date:  1995-10-20       Impact factor: 47.728

9.  Cluster analysis and display of genome-wide expression patterns.

Authors:  M B Eisen; P T Spellman; P O Brown; D Botstein
Journal:  Proc Natl Acad Sci U S A       Date:  1998-12-08       Impact factor: 11.205

10.  Cytotoxic lymphocyte gene expression in peripheral blood leukocytes correlates with rejecting renal allografts.

Authors:  L M Vasconcellos; A D Schachter; X X Zheng; L H Vasconcellos; M Shapiro; W E Harmon; T B Strom; D Schachter
Journal:  Transplantation       Date:  1998-09-15       Impact factor: 4.939

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  2 in total

1.  A novel urine peptide biomarker-based algorithm for the prognosis of necrotising enterocolitis in human infants.

Authors:  Karl G Sylvester; Xuefeng B Ling; G Y Liu; Zachary J Kastenberg; Jun Ji; Zhongkai Hu; Sihua Peng; Ken Lau; Fizan Abdullah; Mary L Brandt; Richard A Ehrenkranz; Mary Catherine Harris; Timothy C Lee; Joyce Simpson; Corinna Bowers; R Lawrence Moss
Journal:  Gut       Date:  2013-09-18       Impact factor: 23.059

2.  A diagnostic algorithm combining clinical and molecular data distinguishes Kawasaki disease from other febrile illnesses.

Authors:  Xuefeng B Ling; Kenneth Lau; John T Kanegaye; Zheng Pan; Sihua Peng; Jun Ji; Gigi Liu; Yuichiro Sato; Tom T S Yu; John C Whitin; James Schilling; Jane C Burns; Harvey J Cohen
Journal:  BMC Med       Date:  2011-12-06       Impact factor: 8.775

  2 in total

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