Literature DB >> 12664686

Assessing the functional bias of commercial microarrays using the onto-compare database.

Sorin Draghici1, Purvesh Khatri, Abhik Shah, Michael A Tainsky.   

Abstract

Microarrays are at the center of a revolution in biotechnology, allowing researchers to screen tens of thousands of genes simultaneously. Typically, they have been used in exploratory research to help formulate hypotheses. In most cases, this phase is followed by a more focused, hypothesis-driven stage in which certain specific biological processes and pathways are thought to be involved. Since a single biological process can still involve hundreds of genes, microarrays are still the preferred approach as proven by the availability of focused arrays from several manufacturers. Because focused arrays from different manufacturers use different sets of genes, each array will represent any given regulatory pathway to a different extent. We argue that a functional analysis of the arrays available should be the most important criterion used in the array selection. We developed Onto-Compare as a database that can provide this functionality, based on the Gene Ontology Consortium nomenclature. We used this tool to compare several arrays focused on apoptosis, oncogenes, and tumor suppressors. We considered arrays from BD Biosciences Clontech, PerkinElmer, Sigma-Genosys, and SuperArray. We showed that among the oncogene arrays, the PerkinElmer MICROMAX oncogene microarray has a better representation of oncogenesis, protein phosphorylation, and negative control of cell proliferation. The comparison of the apoptosis arrays showed that most apoptosis-related biological processes are equally well represented on the arrays considered. However, functional categories such as immune response, cell-cell signaling, cell-surface receptor linked signal transduction, and interleukins are better represented on the Sigma-Genoys Panorama human apoptosis array. At the same time, processes such as cell cycle control, oncogenesis, and negative control of cell proliferation are better represented on the BD Biosciences Clontech Atlas Select human apoptosis array.

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Year:  2003        PMID: 12664686

Source DB:  PubMed          Journal:  Biotechniques        ISSN: 0736-6205            Impact factor:   1.993


  8 in total

1.  Onto-Tools: an ensemble of web-accessible, ontology-based tools for the functional design and interpretation of high-throughput gene expression experiments.

Authors:  Purvesh Khatri; Pratik Bhavsar; Gagandeep Bawa; Sorin Draghici
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

2.  Babel's tower revisited: a universal resource for cross-referencing across annotation databases.

Authors:  Sorin Drăghici; Sivakumar Sellamuthu; Purvesh Khatri
Journal:  Bioinformatics       Date:  2006-10-26       Impact factor: 6.937

3.  Quality Weighted Mean and T-test in Microarray Analysis Lead to Improved Accuracy in Gene Expression Measurements and Reduced Type I and II Errors in Differential Expression Detection.

Authors:  Shouguo Gao; Shuang Jia; Martin Hessner; Xujing Wang
Journal:  J Comput Sci Syst Biol       Date:  2008-12-26

4.  Recent additions and improvements to the Onto-Tools.

Authors:  Purvesh Khatri; Sivakumar Sellamuthu; Pooja Malhotra; Kashyap Amin; Arina Done; Sorin Draghici
Journal:  Nucleic Acids Res       Date:  2005-07-01       Impact factor: 16.971

5.  New Onto-Tools: Promoter-Express, nsSNPCounter and Onto-Translate.

Authors:  Purvesh Khatri; Valmik Desai; Adi L Tarca; Sivakumar Sellamuthu; Derek E Wildman; Roberto Romero; Sorin Draghici
Journal:  Nucleic Acids Res       Date:  2006-07-01       Impact factor: 16.971

6.  Comprehensive quality control utilizing the prehybridization third-dye image leads to accurate gene expression measurements by cDNA microarrays.

Authors:  Xujing Wang; Shuang Jia; Lisa Meyer; Bixia Xiang; Li-Yen Chen; Nan Jiang; Carol Moreno; Howard J Jacob; Soumitra Ghosh; Martin J Hessner
Journal:  BMC Bioinformatics       Date:  2006-08-14       Impact factor: 3.169

7.  Onto-Tools: new additions and improvements in 2006.

Authors:  Purvesh Khatri; Calin Voichita; Khalid Kattan; Nadeem Ansari; Avani Khatri; Constantin Georgescu; Adi L Tarca; Sorin Draghici
Journal:  Nucleic Acids Res       Date:  2007-06-21       Impact factor: 16.971

8.  Cross-species global and subset gene expression profiling identifies genes involved in prostate cancer response to selenium.

Authors:  Michael Schlicht; Brian Matysiak; Tracy Brodzeller; Xinyu Wen; Hang Liu; Guohui Zhou; Rajiv Dhir; Martin J Hessner; Peter Tonellato; Mark Suckow; Morris Pollard; Milton W Datta
Journal:  BMC Genomics       Date:  2004-08-20       Impact factor: 3.969

  8 in total

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