Literature DB >> 12454640

Microarray databases: standards and ontologies.

Christian J Stoeckert1, Helen C Causton, Catherine A Ball.   

Abstract

A single microarray can provide information on the expression of tens of thousands of genes. The amount of information generated by a microarray-based experiment is sufficiently large that no single study can be expected to mine each nugget of scientific information. As a consequence, the scale and complexity of microarray experiments require that computer software programs do much of the data processing, storage, visualization, analysis and transfer. The adoption of common standards and ontologies for the management and sharing of microarray data is essential and will provide immediate benefit to the research community.

Mesh:

Year:  2002        PMID: 12454640     DOI: 10.1038/ng1028

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  28 in total

1.  GEPAS: A web-based resource for microarray gene expression data analysis.

Authors:  Javier Herrero; Fátima Al-Shahrour; Ramón Díaz-Uriarte; Alvaro Mateos; Juan M Vaquerizas; Javier Santoyo; Joaquín Dopazo
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

2.  Exploring the portability of informatics capabilities from a clinical application to a bioscience application.

Authors:  Mark A Shifman; Ranjana Srivastava; Cynthia A Brandt; Tong-Ruei Li; Kevin White; Perry L Miller
Journal:  J Am Med Inform Assoc       Date:  2004-04-02       Impact factor: 4.497

3.  A guide to building image-centric databases.

Authors:  William Bug; Jonathan Nissanov
Journal:  Neuroinformatics       Date:  2003

4.  A method of microarray data storage using array data type.

Authors:  Lam C Tsoi; W Jim Zheng
Journal:  Comput Biol Chem       Date:  2007-01-12       Impact factor: 2.877

5.  Impact of chromosome 17q deletion in the primary lesion of colorectal cancer on liver metastasis.

Authors:  Masaya Kawai; Hiromitsu Komiyama; Masaki Hosoya; Haruna Okubo; Tomoaki Fujii; Norihiko Yokoyama; Chiyo Sato; Takae Ueyama; Atsushi Okuzawa; Michitoshi Goto; Yutaka Kojima; Makoto Takahashi; Kiichi Sugimoto; Shun Ishiyama; Shinya Munakata; Dai Ogura; Shin-Ichiro Niwa; Yuichi Tomiki; Takumi Ochiai; Kazuhiro Sakamoto
Journal:  Oncol Lett       Date:  2016-10-17       Impact factor: 2.967

6.  SGMD: the Soybean Genomics and Microarray Database.

Authors:  Nadim W Alkharouf; Benjamin F Matthews
Journal:  Nucleic Acids Res       Date:  2004-01-01       Impact factor: 16.971

Review 7.  Microarray analysis: a novel research tool for cardiovascular scientists and physicians.

Authors:  C Napoli; L O Lerman; V Sica; A Lerman; G Tajana; F de Nigris
Journal:  Heart       Date:  2003-06       Impact factor: 5.994

8.  Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data.

Authors:  Duane C Hassane; Monica L Guzman; Cheryl Corbett; Xiaojie Li; Ramzi Abboud; Fay Young; Jane L Liesveld; Martin Carroll; Craig T Jordan
Journal:  Blood       Date:  2008-02-27       Impact factor: 22.113

Review 9.  Data standards for Omics data: the basis of data sharing and reuse.

Authors:  Stephen A Chervitz; Eric W Deutsch; Dawn Field; Helen Parkinson; John Quackenbush; Phillipe Rocca-Serra; Susanna-Assunta Sansone; Christian J Stoeckert; Chris F Taylor; Ronald Taylor; Catherine A Ball
Journal:  Methods Mol Biol       Date:  2011

10.  TranscriptomeBrowser: a powerful and flexible toolbox to explore productively the transcriptional landscape of the Gene Expression Omnibus database.

Authors:  Fabrice Lopez; Julien Textoris; Aurélie Bergon; Gilles Didier; Elisabeth Remy; Samuel Granjeaud; Jean Imbert; Catherine Nguyen; Denis Puthier
Journal:  PLoS One       Date:  2008-12-23       Impact factor: 3.240

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