Discovering semantic features in the literature: a foundation for building functional associations |
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Authors: | Monica Chagoyen Pedro Carmona-Saez Hagit Shatkay Jose M Carazo and Alberto Pascual-Montano |
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Institution: | (1) Biocomputing Unit, Centro Nacional de Biotecnologia – CSIC, Madrid, Spain;(2) School of Computing, Queen's University, Kingston, Ontario, Canada;(3) Dpto. Arquitectura de Computadores, Universidad Complutense de Madrid, Madrid, Spain |
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Abstract: | Background Experimental techniques such as DNA microarray, serial analysis of gene expression (SAGE) and mass spectrometry proteomics,
among others, are generating large amounts of data related to genes and proteins at different levels. As in any other experimental
approach, it is necessary to analyze these data in the context of previously known information about the biological entities
under study. The literature is a particularly valuable source of information for experiment validation and interpretation.
Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in
current bioinformatics research. |
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Keywords: | |
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