GNPS

GNPS facilitates organization, sharing, and community annotation of mass spectrometry (MS/MS) data to support identification and discovery of natural products.

Key Features:

• MS/MS data organization: Handles raw, processed, and annotated MS/MS datasets for community-wide aggregation.
• Community reference MS libraries: Integrates community-wide reference MS libraries for spectral matching and annotation.
• Crowdsourced curation: Enables crowdsourced curation of spectra to improve annotation quality through community contributions.
• Living data: Performs continuous reanalysis of deposited datasets to update and refine annotations over time.
• Data-driven social networking: Connects researchers and datasets through data-driven social networking to facilitate collaborative analysis.
• Support for high-throughput MS characterization: Leverages mass spectrometry techniques suitable for high-throughput characterization of natural products.

Scientific Applications:

• Natural product identification: Supports spectral identification and discovery workflows for natural products (NP).
• Spectral annotation improvement: Improves annotation accuracy by combining reference library matches with community-curated spectra.
• Post-publication reanalysis: Enables reanalysis of published or deposited MS/MS datasets to derive new or updated annotations.
• Community curation and library expansion: Facilitates expansion and refinement of MS reference libraries through community contributions.

Methodology:

Molecular networking and organization/sharing of raw, processed, and annotated MS/MS data, crowdsourced curation using community reference MS libraries, and continuous reanalysis of deposited datasets ("living data").