CleanEx: a database of heterogeneous gene expression data based on a consistent gene nomenclature

Area of Science:

• Bioinformatics
• Genomics
• Molecular Biology

Background:

• Public gene expression data is often heterogeneous, hindering joint analysis and cross-dataset comparisons.
• A consistent gene nomenclature is crucial for integrating and interpreting diverse expression datasets.

Purpose of the Study:

• To provide unified access to public gene expression data through unique gene names.
• To represent heterogeneous expression data from various technologies for joint analysis.
• To facilitate cross-dataset comparisons of gene expression profiles.

Main Methods:

• Associating experiments with permanent target identifiers for consistent gene nomenclature.
• Mapping targets to evolving gene catalogs of human and model organisms using external resources (UniGene, RefSeq).
• Utilizing a weekly updated gene index and an expression target database for mapping and quality control.

Main Results:

• CleanEx provides a central gene index with cross-references to incorporated public expression data.
• The expression target database offers gene mapping and quality control for experimental resources (e.g., cDNA clones, Affymetrix probe sets).
• Web-based query interfaces allow access via text searches and quantitative expression criteria.

Conclusions:

• CleanEx successfully integrates and standardizes heterogeneous public gene expression data.
• The system facilitates comparative analysis and data mining across different experimental platforms and organisms.
• CleanEx serves as a valuable resource for researchers in genomics and molecular biology.