Artículo

Perelman, S.; Mazzella, M.A.; Muschietti, J.; Zhu, T.; Casal, J.J. "Finding Unexpected Patterns in Microarray Data" (2003) Plant Physiology. 133(4):1717-1725
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Abstract:

We describe the performance of a protocol based on the sequential application of unsupervised and supervised methods to analyze microarray samples defined by a combination of factors. Correspondence analysis is used to visualize the emerging patterns of three set of novel or previously published data: photoreceptor mutants of Arabidopsis grown under different light/dark conditions, Arabidopsis exposed to different types of biotic and abiotic stress, and human acute leukemia. We find, for instance, that light has a dramatic effect on plants despite the absence of the four major photoreceptors, that bacterial-, fungal-, and viral-induced responses converge at later stages of attack, and that sample preparation procedures used in different hospitals have large effects on transcriptome patterns. We use canonical discriminant analysis to identify the genes associated with these patters and hierarchical clustering to find groups of coregulated genes that are easily visualized in a second round of correspondence analysis and ordered tables. The unconventional combination of standard descriptive multivariate methods offers a previously unrecognized tool to uncover unexpected information.

Registro:

Documento: Artículo
Título:Finding Unexpected Patterns in Microarray Data
Autor:Perelman, S.; Mazzella, M.A.; Muschietti, J.; Zhu, T.; Casal, J.J.
Filiación:IFEVA, Facultad de Agronomía, Universidad de Buenos Aires, Av. San Martín 4453, 1417-Buenos Aires, Argentina
Inst. Invest. Ing. Genet. Biol. M., Vuelta de Obligado 2490, 1428-Buenos Aires, Argentina
Syngenta Biotechnology, Inc., 3054 Cornwallis Road, Research Triangle Park, NC 27709, United States
Palabras clave:Bacteria; Fungi; Genes; Hospitals; Physiology; Viruses; Microarray data; Plants (botany); Arabidopsis protein; Arabidopsis; article; automated pattern recognition; biology; DNA microarray; gene; gene deletion; genetic transcription; genetics; light; methodology; photosynthesis; physiology; Arabidopsis; Arabidopsis Proteins; Computational Biology; Gene Deletion; Genes, Plant; Light; Oligonucleotide Array Sequence Analysis; Pattern Recognition, Automated; Photosynthetic Reaction Center Complex Proteins; Transcription, Genetic; Arabidopsis; Bacteria (microorganisms); Fungi
Año:2003
Volumen:133
Número:4
Página de inicio:1717
Página de fin:1725
DOI: http://dx.doi.org/10.1104/pp.103.028753
Título revista:Plant Physiology
Título revista abreviado:Plant Physiol.
ISSN:00320889
CODEN:PLPHA
CAS:Arabidopsis Proteins; Photosynthetic Reaction Center Complex Proteins
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00320889_v133_n4_p1717_Perelman

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Citas:

---------- APA ----------
Perelman, S., Mazzella, M.A., Muschietti, J., Zhu, T. & Casal, J.J. (2003) . Finding Unexpected Patterns in Microarray Data. Plant Physiology, 133(4), 1717-1725.
http://dx.doi.org/10.1104/pp.103.028753
---------- CHICAGO ----------
Perelman, S., Mazzella, M.A., Muschietti, J., Zhu, T., Casal, J.J. "Finding Unexpected Patterns in Microarray Data" . Plant Physiology 133, no. 4 (2003) : 1717-1725.
http://dx.doi.org/10.1104/pp.103.028753
---------- MLA ----------
Perelman, S., Mazzella, M.A., Muschietti, J., Zhu, T., Casal, J.J. "Finding Unexpected Patterns in Microarray Data" . Plant Physiology, vol. 133, no. 4, 2003, pp. 1717-1725.
http://dx.doi.org/10.1104/pp.103.028753
---------- VANCOUVER ----------
Perelman, S., Mazzella, M.A., Muschietti, J., Zhu, T., Casal, J.J. Finding Unexpected Patterns in Microarray Data. Plant Physiol. 2003;133(4):1717-1725.
http://dx.doi.org/10.1104/pp.103.028753