Mining Microarray Expression Data by Literature Profiling

Authors: Damien Chaussabel and Alan Sher (Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health)

Description: The authors developed a mining technique based on the analysis of literature profiles generated by extracting the frequencies of certain terms from thousands of abstracts stored in the Medline literature database. Terms are then filtered on the basis of both repetitive occurrence and co-occurrence among multiple gene entries. Finally, clustering analysis is performed on the retained frequency values, shaping a coherent picture of the functional relationship among large and heterogeneous lists of genes. Such data treatment also provides information on the nature and pertinence of the associations that were formed.The analysis of patterns of term occurrence in abstracts constitutes a means of exploring the biological significance of large and heterogeneous lists of genes. This approach should contribute to optimizing the exploitation of microarray technologies by providing investigators with an interface between complex expression data and large literature resources.

Full reference: Chaussabel, D., & Sher, A. (2001). Mining microarray expression data by literature profiling.Genome Biology, 3, 1-55.

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