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eVOC: A Controlled Vocabulary for Unifying Gene Expression Data
Author(s) -
Janet Kelso,
Johann Visagie,
Grégory Theiler,
Alan Christoffels,
Soraya Bardien,
Damian Smedley,
Darren Otgaar,
Gary Greyling,
C. Victor Jongeneel,
Mark I. McCarthy,
Tania Hide,
Yoshihide Hayashizaki
Publication year - 2003
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.985203
Subject(s) - biology , expression (computer science) , vocabulary , controlled vocabulary , expressed sequence tag , gene nomenclature , computational biology , microarray databases , set (abstract data type) , human genome , serial analysis of gene expression , gene annotation , information retrieval , dna microarray , gene expression profiling , computer science , gene , genetics , gene expression , genome , linguistics , taxonomy (biology) , philosophy , botany , nomenclature , programming language
Expression data contribute significantly to the biological value of the sequenced human genome, providing extensive information about gene structure and the pattern of gene expression. ESTs, together with SAGE libraries and microarray experiment information, provide a broad and rich view of the transcriptome. However, it is difficult to perform large-scale expression mining of the data generated by these diverse experimental approaches. Not only is the data stored in disparate locations, but there is frequent ambiguity in the meaning of terms used to describe the source of the material used in the experiment. Untangling semantic differences between the data provided by different resources is therefore largely reliant on the domain knowledge of a human expert. We present here eVOC, a system which associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. We have curated and annotated 7016 cDNA libraries represented in dbEST, as well as 104 SAGE libraries,with expression information,and provide this as an integrated, public resource that allows the linking of transcripts and libraries with expression terms. Both the vocabularies and the vocabulary-annotated libraries can be retrieved from http://www.sanbi.ac.za/evoc/. Several groups are involved in developing this resource with the aim of unifying transcript expression information.

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