Literature DB >> 10779484

Systematic management and analysis of yeast gene expression data.

J Aach1, W Rindone, G M Church.   

Abstract

We report steps toward the systematic management, standardization, and analysis of functional genomics data. We developed the ExpressDB database for yeast RNA expression data and loaded it with approximately 17.5 million pieces of data reported by 11 studies with three different kinds of high-throughput RNA assays. A web-based tool supports queries across the data from these studies. We examined comparability of data by converting data from 9 studies (217 conditions) into mRNA relative abundance estimates (ERAs) and by clustering of conditions by ERAs. We report on generation of ERAs and condition clustering for non-microarray data (5 studies, 63 conditions) and describe initial attempts to generate microarray-based ERAs (4 studies, 154 conditions), which exhibit increased error, on our web site http://arep.med.harvard. edu/ExpressDB. We recommend standards for data reporting, suggest research into improving comparability of microarray data through quantifying and standardizing control condition RNA populations, and also suggest research into the calibration of different RNA assays. We introduce a model for a database that integrates different kinds of functional genomics data, Biomolecule Interaction, Growth and Expression Database (BIGED).

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Year:  2000        PMID: 10779484     DOI: 10.1101/gr.10.4.431

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  37 in total

1.  PartsList: a web-based system for dynamically ranking protein folds based on disparate attributes, including whole-genome expression and interaction information.

Authors:  J Qian; B Stenger; C A Wilson; J Lin; R Jansen; S A Teichmann; J Park; W G Krebs; H Yu; V Alexandrov; N Echols; M Gerstein
Journal:  Nucleic Acids Res       Date:  2001-04-15       Impact factor: 16.971

2.  An evaluation of the performance of cDNA microarrays for detecting changes in global mRNA expression.

Authors:  H Yue; P S Eastman; B B Wang; J Minor; M H Doctolero; R L Nuttall; R Stack; J W Becker; J R Montgomery; M Vainer; R Johnston
Journal:  Nucleic Acids Res       Date:  2001-04-15       Impact factor: 16.971

3.  SPINE: an integrated tracking database and data mining approach for identifying feasible targets in high-throughput structural proteomics.

Authors:  P Bertone; Y Kluger; N Lan; D Zheng; D Christendat; A Yee; A M Edwards; C H Arrowsmith; G T Montelione; M Gerstein
Journal:  Nucleic Acids Res       Date:  2001-07-01       Impact factor: 16.971

4.  yMGV: helping biologists with yeast microarray data mining.

Authors:  Stéphane Le Crom; Frédéric Devaux; Claude Jacq; Philippe Marc
Journal:  Nucleic Acids Res       Date:  2002-01-01       Impact factor: 16.971

5.  Argus--a new database system for Web-based analysis of multiple microarray data sets.

Authors:  J Comander; G M Weber; M A Gimbrone; G García-Cardeña
Journal:  Genome Res       Date:  2001-09       Impact factor: 9.043

6.  Measuring absolute expression with microarrays with a calibrated reference sample and an extended signal intensity range.

Authors:  Aimée M Dudley; John Aach; Martin A Steffen; George M Church
Journal:  Proc Natl Acad Sci U S A       Date:  2002-05-28       Impact factor: 11.205

7.  yMGV: a database for visualization and data mining of published genome-wide yeast expression data.

Authors:  P Marc; F Devaux; C Jacq
Journal:  Nucleic Acids Res       Date:  2001-07-01       Impact factor: 16.971

8.  Global RNA half-life analysis in Escherichia coli reveals positional patterns of transcript degradation.

Authors:  Douglas W Selinger; Rini Mukherjee Saxena; Kevin J Cheung; George M Church; Carsten Rosenow
Journal:  Genome Res       Date:  2003-02       Impact factor: 9.043

9.  Judging the quality of gene expression-based clustering methods using gene annotation.

Authors:  Francis D Gibbons; Frederick P Roth
Journal:  Genome Res       Date:  2002-10       Impact factor: 9.043

10.  Comparative analysis of multiple genome-scale data sets.

Authors:  Margaret Werner-Washburne; Brian Wylie; Kevin Boyack; Edwina Fuge; Judith Galbraith; Jose Weber; George Davidson
Journal:  Genome Res       Date:  2002-10       Impact factor: 9.043

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