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Treffer: GEDI: a user-friendly toolbox for analysis of large-scale gene expression data.

Title:
GEDI: a user-friendly toolbox for analysis of large-scale gene expression data.
Authors:
Fujita A; Chemistry Institute, University of São Paulo, Av, Lineu Prestes, 748 - São Paulo, 05508-900, SP, Brazil. fujita@ime.usp.br, Sato JR, Ferreira CE, Sogayar MC
Source:
BMC bioinformatics [BMC Bioinformatics] 2007 Nov 19; Vol. 8, pp. 457. Date of Electronic Publication: 2007 Nov 19.
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105 (Electronic) Linking ISSN: 14712105 NLM ISO Abbreviation: BMC Bioinformatics Subsets: MEDLINE
Imprint Name(s):
Original Publication: [London] : BioMed Central, 2000-
MeSH Terms:
Algorithms* , Artificial Intelligence* , Software* , User-Computer Interface*, Chromosome Mapping/*methods , Gene Expression Profiling/*methods , Oligonucleotide Array Sequence Analysis/*methods , Pattern Recognition, Automated/*methods, Computer Graphics
References:
Bioinformatics. 2001;17 Suppl 1:S316-22. (PMID: 11473023)
Bioinformatics. 2007 Feb 15;23(4):442-9. (PMID: 17158516)
Proc Natl Acad Sci U S A. 2001 Apr 24;98(9):5116-21. (PMID: 11309499)
Bioinformatics. 2004 Nov 22;20(17):3196-205. (PMID: 15231532)
BMC Syst Biol. 2007 Aug 30;1:39. (PMID: 17761000)
Bioinformatics. 2007 Jul 1;23(13):1623-30. (PMID: 17463021)
Genome Biol. 2002 Aug 30;3(9):research0048. (PMID: 12225587)
Comb Chem High Throughput Screen. 2004 Dec;7(8):783-91. (PMID: 15578940)
Nucleic Acids Res. 2002 Feb 15;30(4):e15. (PMID: 11842121)
Bioinformatics. 2003 Jan 22;19(2):185-93. (PMID: 12538238)
BMC Bioinformatics. 2006 Oct 23;7:469. (PMID: 17059609)
Entry Date(s):
Date Created: 20071121 Date Completed: 20080204 Latest Revision: 20230412
Update Code:
20250114
PubMed Central ID:
PMC2194737
DOI:
10.1186/1471-2105-8-457
PMID:
18021455
Database:
MEDLINE

Weitere Informationen

Background: Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills.
Results: Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al.
Conclusion: GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.