CoPub

CoPub performs literature-based gene–keyword correlation analysis using Medline to support biological interpretation of microarray data from human, mouse, and rat.

Key Features:

• Batch Input Capability: Accepts batch submission of multiple genes from human, mouse, or rat for collective analysis.
• Keyword Correlation Analysis: Generates lists of keywords from biomedical thesauri (including biological processes, pathways, drugs, pathologies, and diseases) that are significantly correlated with the input gene set.
• Linking to Medline Abstracts: Links identified keywords and co-occurring genes to Medline abstracts and highlights their co-occurrence within abstracts.
• Graphical Visualization: Displays differentially expressed genes and over-represented keywords in a network-format visualization that identifies highly connected genes as influential hubs.
• Statistical Analysis: Applies statistical methods to determine significant correlations between genes and keywords.
• Microarray Data Support: Facilitates interpretation specifically of microarray-derived gene expression results.

Scientific Applications:

• Gene Expression Analysis: Identifies and contextualizes differentially expressed genes from microarray experiments using literature-derived associations.
• Pathway and Process Identification: Reveals pathways and biological processes associated with gene sets by linking genes to relevant thesaurus terms.
• Drug and Disease Research: Connects genes to drugs, pathologies, and diseases to inform investigations of therapeutic targets and disease mechanisms.

Methodology:

Extracts gene–keyword co-occurrences from the Medline database, employs statistical methods to identify significant correlations, and constructs network-based visualizations of genes and keywords.