PomBase

PomBase curates and integrates genetic, molecular, and cell biological data for the fission yeast Schizosaccharomyces pombe to support experimental and computational research.

Key Features:

• Model organism database (MOD): Serves as the MOD for Schizosaccharomyces pombe by aggregating curated genetic, molecular, and cell biological knowledge.
• Integration of standardized published data: Integrates standardized published data into an online database format.
• Community curation with Canto: Employs the Canto online curation tool to capture author-contributed annotations using shared ontologies.
• Shared ontologies: Uses shared ontologies to describe functional data and annotations.
• Manual literature curation and co-curation: Provides comprehensive manual literature curation combined with co-curation by publication authors and professional curators.
• Annotation of genomic sequences and features: Annotates genomic sequences and sequence features for Schizosaccharomyces pombe.
• Genome-wide datasets: Incorporates genome-wide datasets relevant to fission yeast research.
• User-defined and novel query capabilities: Supports sophisticated user-defined queries and novel query capabilities for retrieving curated data.
• Data summaries and visualizations: Provides data summaries and visualizations to aid biological interpretation of curated datasets.
• Community curation metrics: Maintains a community curation program with eight years of activity and a reported ~50% author response rate.

Scientific Applications:

• Knowledge integration for S. pombe research: Provides integrated genetic, molecular, and cell biological knowledge to support experimental design and interpretation in Schizosaccharomyces pombe and related studies.
• Incorporation of hypothesis-driven data: Enables incorporation of detailed functional data from hypothesis-driven experiments into curated annotations.
• Functional annotation using ontologies: Supports ontology-based functional annotation of gene products and biological processes.
• Genomic and genome-wide analysis: Facilitates analysis and interpretation of genome-wide datasets and annotated genomic features.
• Query-driven data retrieval for downstream analysis: Enables retrieval of curated datasets via user-defined queries for downstream computational and experimental analyses.

Methodology:

Integration of standardized published data into an online database; use of the Canto online curation tool with shared ontologies for community curation; manual literature curation and annotation of genomic sequences and features; incorporation of genome-wide datasets with support for user-defined queries and data visualizations.