Literature DB >> 15052631

Digital quantitative measurements of gene expression.

Venugopal Mikkilineni1, Robi D Mitra, Joshua Merritt, Jason R DiTonno, George M Church, Babatunde Ogunnaike, Jeremy S Edwards.   

Abstract

One of the primary goals of functional genomics is to provide a quantitative understanding of gene function. However, the success of this enterprise is dependent on the accuracy and precision of the functional genomic data. A novel approach, digital analysis of gene expression (DAGE) described herein, is an accurate and precise technology for measuring digital gene expression on a relative or absolute scale by simply counting the number of transcripts of a gene being expressed at a given time. The result is a greatly improved technology sensitive enough for identifying and quantifying small (but biologically important and statistically relevant) changes in gene expression. Fourteen genes involved in galactose metabolism in Saccharomyces cerevisiae were analyzed for their expression levels in glucose and galactose minimal media. The quantitative expression results were characterized in terms of distributional and accuracy attributes; they were also in general agreement (in terms of direction of change) with corresponding results obtained using microarray technology. DAGE is likely to have profound implications in the field of functional genomics because the gene expression measurements are digital in nature and therefore more accurate than any other technologies. Copyright 2004 Wiley Periodicals, Inc.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15052631     DOI: 10.1002/bit.20048

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  5 in total

Review 1.  Methods for transcriptional profiling in plants. Be fruitful and replicate.

Authors:  Blake C Meyers; David W Galbraith; Timothy Nelson; Vikas Agrawal
Journal:  Plant Physiol       Date:  2004-06-01       Impact factor: 8.340

2.  Parallel analysis of tetramerization domain mutants of the human p53 protein using PCR colonies.

Authors:  Joshua Merritt; Kim G Roberts; James A Butz; Jeremy S Edwards
Journal:  Genomic Med       Date:  2007-09-05

3.  Next-generation sequencing library construction on a surface.

Authors:  Kuan Feng; Justin Costa; Jeremy S Edwards
Journal:  BMC Genomics       Date:  2018-05-30       Impact factor: 3.969

4.  Polony analysis of gene expression in ES cells and blastocysts.

Authors:  C Rieger; R Poppino; R Sheridan; K Moley; R Mitra; D Gottlieb
Journal:  Nucleic Acids Res       Date:  2007-12-10       Impact factor: 16.971

5.  Genomic convergence analysis of schizophrenia: mRNA sequencing reveals altered synaptic vesicular transport in post-mortem cerebellum.

Authors:  Joann Mudge; Neil A Miller; Irina Khrebtukova; Ingrid E Lindquist; Gregory D May; Jim J Huntley; Shujun Luo; Lu Zhang; Jennifer C van Velkinburgh; Andrew D Farmer; Sharon Lewis; William D Beavis; Faye D Schilkey; Selene M Virk; C Forrest Black; M Kathy Myers; Lar C Mader; Ray J Langley; John P Utsey; Ryan W Kim; Rosalinda C Roberts; Sat Kirpal Khalsa; Meredith Garcia; Victoria Ambriz-Griffith; Richard Harlan; Wendy Czika; Stanton Martin; Russell D Wolfinger; Nora I Perrone-Bizzozero; Gary P Schroth; Stephen F Kingsmore
Journal:  PLoS One       Date:  2008-11-05       Impact factor: 3.240

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.