Mining microarray expression data by literature profiling.

ABSTRACT:

Background

The rapidly expanding fields of genomics and proteomics have prompted the development of computational methods for managing, analyzing and visualizing expression data derived from microarray screening. Nevertheless, the lack of efficient techniques for assessing the biological implications of gene-expression data remains an important obstacle in exploiting this information.

Results

To address this need, we have 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 o

SUBMITTER: Chaussabel D 

PROVIDER: S-EPMC134484 | biostudies-literature | 2002 Sep

REPOSITORIES: biostudies-literature