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A GIS methodological framework based on fuzzy sets theory for land use management

Ordering Gene Expression Data Using One-Dimensional Self-Organizing Maps

Dmitry KurtenerVladimir Badenko

Lalinka de C. T. GomesFernando J. Von ZubenPablo Moscato

This paper considers a GIS methodological framework based on fuzzy sets theory for land use management. Some principles of development of the GIS methodological framework are formulated. Applications of the GIS methodological framework are designed. In particular GIS knowledge management fuzzy models for analysis of soil commutative contamination by heavy metals, for the study of soil acidity, and for evaluation of soil conservation actions are obtained. The microarray technology allows researchers to simultaneously measure gene expression levels of thousands of genes. Analysis of data produced by such experiments provides knowledge about the gene function. An important step in the analysis of gene expression data is the detection of genes with similar expression patterns. Real-time computational tools for organization and visualization are crucial to understand and analyze the data. In this work, we make use of an algorithm based on self-organizing neural networks for organizing gene expression data in order to reveal trends in gene expression profiles under the biological viewpoint.

http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002000000100004&lng=e

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