Literature DB >> 12450790

Optimal gene expression analysis by microarrays.

Lance D Miller1, Philip M Long, Limsoon Wong, Sayan Mukherjee, Lisa M McShane, Edison T Liu.   

Abstract

DNA microarrays make possible the rapid and comprehensive assessment of the transcriptional activity of a cell, and as such have proven valuable in assessing the molecular contributors to biological processes and in the classification of human cancers. The major challenge in using this technology is the analysis of its massive data output, which requires computational means for interpretation and a heightened need for quality data. The optimal analysis requires an accounting and control of the many sources of variance within the system, an understanding of the limitations of the statistical approaches, and the ability to make sense of the results through intelligent database interrogation.

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Year:  2002        PMID: 12450790     DOI: 10.1016/s1535-6108(02)00181-2

Source DB:  PubMed          Journal:  Cancer Cell        ISSN: 1535-6108            Impact factor:   31.743


  48 in total

1.  Spurious spatial periodicity of co-expression in microarray data due to printing design.

Authors:  Gábor Balázsi; Krin A Kay; Albert-László Barabási; Zoltán N Oltvai
Journal:  Nucleic Acids Res       Date:  2003-08-01       Impact factor: 16.971

Review 2.  New approaches to investigating heterogeneity in complex traits.

Authors:  R Bomprezzi; P E Kovanen; R Martin
Journal:  J Med Genet       Date:  2003-08       Impact factor: 6.318

Review 3.  Statistical issues in the design and analysis of gene expression microarray studies of animal models.

Authors:  Lisa M McShane; Joanna H Shih; Aleksandra M Michalowska
Journal:  J Mammary Gland Biol Neoplasia       Date:  2003-07       Impact factor: 2.673

Review 4.  The microarray data analysis process: from raw data to biological significance.

Authors:  N Eric Olson
Journal:  NeuroRx       Date:  2006-07

5.  Comprehensive gene and microRNA expression profiling reveals the crucial role of hsa-let-7i and its target genes in colorectal cancer metastasis.

Authors:  Peng Zhang; Yanlei Ma; Feng Wang; Jianjun Yang; Zhihua Liu; Jiayuan Peng; Huanlong Qin
Journal:  Mol Biol Rep       Date:  2011-05-29       Impact factor: 2.316

6.  RRAS: A key regulator and an important prognostic biomarker in biliary atresia.

Authors:  Rui Zhao; Hao Li; Chun Shen; Shan Zheng
Journal:  World J Gastroenterol       Date:  2011-02-14       Impact factor: 5.742

7.  Distance-based classifiers as potential diagnostic and prediction tools for human diseases.

Authors:  Boris Veytsman; Lei Wang; Tiange Cui; Sergey Bruskin; Ancha Baranova
Journal:  BMC Genomics       Date:  2014-12-19       Impact factor: 3.969

8.  Understanding PRRSV infection in porcine lung based on genome-wide transcriptome response identified by deep sequencing.

Authors:  Shuqi Xiao; Jianyu Jia; Delin Mo; Qiwei Wang; Limei Qin; Zuyong He; Xiao Zhao; Yuankai Huang; Anning Li; Jingwei Yu; Yuna Niu; Xiaohong Liu; Yaosheng Chen
Journal:  PLoS One       Date:  2010-06-29       Impact factor: 3.240

9.  Distinct gene-expression profiles characterize mammary tumors developed in transgenic mice expressing constitutively active and C-terminally truncated variants of STAT5.

Authors:  Tali Eilon; Itamar Barash
Journal:  BMC Genomics       Date:  2009-05-18       Impact factor: 3.969

10.  miR-429 identified by dynamic transcriptome analysis is a new candidate biomarker for colorectal cancer prognosis.

Authors:  Yingnan Sun; Shourong Shen; Hailin Tang; Juanjuan Xiang; Ya Peng; Anliu Tang; Nan Li; Weiwei Zhou; Zeyou Wang; Decai Zhang; Bo Xiang; Jie Ge; Guiyuan Li; Minghua Wu; Xiayu Li
Journal:  OMICS       Date:  2013-11-16
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