Candida Genome Database

The Candida Genome Database (CGD) curates genomic data, gene annotations, and experimental literature for pathogenic Candida species to support research on Candida biology, epidemiology, and antifungal treatment development.

Key Features:

• Multi-species locus pages: Hosts locus pages for five species of pathogenic Candida fungi.
• Literature curation: Curates the entire gene-based Candida experimental literature as it is published, extracting, organizing, and standardizing gene annotations.
• Literature Topic tags: Assigns Literature Topic tags focused on aspects related to pathogenicity.
• Mutant phenotype data: Collects detailed mutant phenotype data with controlled Gene Ontology terms and accompanying evidence codes.
• Clinical data linkage: Links clinical data on disease to relevant Literature Topics to improve searchability for clinical researchers.
• Feature Summary pages: Provides primary name and all aliases, gene and/or gene product descriptions, detailed ortholog information with links, JBrowse visualization, summarized phenotype, Gene Ontology, and sequence information, references, and locus notes.
• Community hub resources: Links to reference material including colleague information, news, and upcoming meetings.

Scientific Applications:

• Candida biology research: Supports investigation of basic Candida biology including biofilm formation and morphogenic switching from planktonic to filamentous forms.
• Pathogenicity studies: Enables research on pathogenic mechanisms across multiple Candida species.
• Antifungal drug discovery: Facilitates research into potential new antifungals as pathogenic Candida species become increasingly drug resistant.
• Epidemiology and phylogeny: Supports research into Candida epidemiology and phylogeny.
• Clinical research: Improves searchability of clinical data on disease for clinical researchers.

Methodology:

CGD curators extract, organize, and standardize gene annotations from published experimental literature; assign controlled Gene Ontology terms with evidence codes; collect detailed mutant phenotype data; and assign Literature Topic tags focused on pathogenicity-related aspects.