Literature DB >> 18053704

Microarray-based expression profiling and informatics.

Richard Simon1.   

Abstract

Microarray-based expression profiling is a powerful technology for studying biological mechanisms and for developing clinically valuable predictive classifiers. The high-dimensional read-out for each sample assayed makes it possible to do new kinds of studies but also increases the risks of misleading conclusions. We review here the current state-of-the-art for design and analysis of microarray-based investigations.

Mesh:

Year:  2007        PMID: 18053704      PMCID: PMC2290821          DOI: 10.1016/j.copbio.2007.10.008

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  26 in total

1.  A gene expression-based method to diagnose clinically distinct subgroups of diffuse large B cell lymphoma.

Authors:  George Wright; Bruce Tan; Andreas Rosenwald; Elaine H Hurt; Adrian Wiestner; Louis M Staudt
Journal:  Proc Natl Acad Sci U S A       Date:  2003-08-04       Impact factor: 11.205

2.  Using the gene ontology for microarray data mining: a comparison of methods and application to age effects in human prefrontal cortex.

Authors:  Paul Pavlidis; Jie Qin; Victoria Arango; John J Mann; Etienne Sibille
Journal:  Neurochem Res       Date:  2004-06       Impact factor: 3.996

3.  Effects of pooling mRNA in microarray class comparisons.

Authors:  Joanna H Shih; Aleksandra M Michalowska; Kevin Dobbin; Yumei Ye; Ting Hu Qiu; Jeffrey E Green
Journal:  Bioinformatics       Date:  2004-07-09       Impact factor: 6.937

4.  Sample size determination in microarray experiments for class comparison and prognostic classification.

Authors:  Kevin Dobbin; Richard Simon
Journal:  Biostatistics       Date:  2005-01       Impact factor: 5.899

5.  Prediction error estimation: a comparison of resampling methods.

Authors:  Annette M Molinaro; Richard Simon; Ruth M Pfeiffer
Journal:  Bioinformatics       Date:  2005-05-19       Impact factor: 6.937

6.  Sample size planning for developing classifiers using high-dimensional DNA microarray data.

Authors:  Kevin K Dobbin; Richard M Simon
Journal:  Biostatistics       Date:  2006-04-13       Impact factor: 5.899

7.  Extensions to gene set enrichment.

Authors:  Zhen Jiang; Robert Gentleman
Journal:  Bioinformatics       Date:  2006-11-24       Impact factor: 6.937

8.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Authors:  Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

9.  Bias in error estimation when using cross-validation for model selection.

Authors:  Sudhir Varma; Richard Simon
Journal:  BMC Bioinformatics       Date:  2006-02-23       Impact factor: 3.169

10.  A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets.

Authors:  Carmen Lai; Marcel J T Reinders; Laura J van't Veer; Lodewyk F A Wessels
Journal:  BMC Bioinformatics       Date:  2006-05-02       Impact factor: 3.169

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  14 in total

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Authors:  Ganiraju Manyam; Aybike Birerdinc; Ancha Baranova
Journal:  BMC Syst Biol       Date:  2015-04-15

Review 2.  Genomic profiling of mesenchymal stem cells.

Authors:  Danijela Menicanin; P Mark Bartold; Andrew C W Zannettino; Stan Gronthos
Journal:  Stem Cell Rev Rep       Date:  2009-02-18       Impact factor: 5.739

3.  Neutrophil chemotaxis and transcriptomics in term and preterm neonates.

Authors:  Steven L Raymond; Brittany J Mathias; Tyler J Murphy; Jaimar C Rincon; María Cecilia López; Ricardo Ungaro; Felix Ellett; Julianne Jorgensen; James L Wynn; Henry V Baker; Lyle L Moldawer; Daniel Irimia; Shawn D Larson
Journal:  Transl Res       Date:  2017-09-01       Impact factor: 7.012

4.  Distinct genetic profile in peripheral blood mononuclear cells of psoriatic arthritis patients treated with methotrexate and TNF-inhibitors.

Authors:  Raquel Cuchacovich; Rodolfo Perez-Alamino; Arnold H Zea; Luis R Espinoza
Journal:  Clin Rheumatol       Date:  2014-10-24       Impact factor: 2.980

5.  Association of IFN-gamma signal transduction defects with impaired HLA class I antigen processing in melanoma cell lines.

Authors:  Annedore Respa; Juergen Bukur; Soldano Ferrone; Graham Pawelec; Yingdong Zhao; Ena Wang; Francesco M Marincola; Barbara Seliger
Journal:  Clin Cancer Res       Date:  2011-01-19       Impact factor: 12.531

6.  Algebraic comparison of partial lists in bioinformatics.

Authors:  Giuseppe Jurman; Samantha Riccadonna; Roberto Visintainer; Cesare Furlanello
Journal:  PLoS One       Date:  2012-05-17       Impact factor: 3.240

7.  Expression microarray meta-analysis identifies genes associated with Ras/MAPK and related pathways in progression of muscle-invasive bladder transition cell carcinoma.

Authors:  Jonathan A Ewald; Tracy M Downs; Jeremy P Cetnar; William A Ricke
Journal:  PLoS One       Date:  2013-02-01       Impact factor: 3.240

8.  Immune-Signatures for Lung Cancer Diagnostics: Evaluation of Protein Microarray Data Normalization Strategies.

Authors:  Stefanie Brezina; Regina Soldo; Roman Kreuzhuber; Philipp Hofer; Andrea Gsur; Andreas Weinhaeusel
Journal:  Microarrays (Basel)       Date:  2015-04-02

9.  Antigen stimulation of peripheral blood mononuclear cells from Mycobacterium bovis infected cattle yields evidence for a novel gene expression program.

Authors:  Kieran G Meade; Eamonn Gormley; Cliona O'Farrelly; Stephen D Park; Eamon Costello; Joseph Keane; Yingdong Zhao; David E MacHugh
Journal:  BMC Genomics       Date:  2008-09-29       Impact factor: 3.969

10.  Evidence based selection of commonly used RT-qPCR reference genes for the analysis of mouse skeletal muscle.

Authors:  Kristen C Thomas; Xi Fiona Zheng; Francia Garces Suarez; Joanna M Raftery; Kate G R Quinlan; Nan Yang; Kathryn N North; Peter J Houweling
Journal:  PLoS One       Date:  2014-02-11       Impact factor: 3.240

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