ErrorTracer

ErrorTracer identifies and classifies inconsistencies in genome-scale metabolic models (GEMs), locating reactions incapable of carrying flux and tracing the origins of model errors to support model-quality control.

Key Features:

• Inconsistency detection: Searches GEMs for reactions incapable of carrying flux and other model inconsistencies.
• Classification and origin identification: Classifies inconsistency types and pinpoints their origins within the network model.
• Performance: Provides inconsistency checking approximately two orders of magnitude faster than current community-standard methods for large-scale models.
• Scalability: Analyzes models produced by automated model-generation algorithms and large, complex metabolic networks.
• Gap-filling diagnostics: Detects errors that automated gap-filling algorithms may miss and facilitates automated model-validation workflows.

Scientific Applications:

• Model quality control: Assessing and improving the accuracy and consistency of genome-scale metabolic models (GEMs).
• Metabolic network debugging: Identifying and localizing reactions incapable of carrying flux and related inconsistencies in metabolic reconstructions.
• Validation of automated workflows: Validating models produced by automated model-generation algorithms and diagnosing errors left by automated gap-filling algorithms.
• Pre-publication model validation: Supporting automated model-validation prior to publication.

Methodology:

Performs model-wide inconsistency searches, classifies inconsistency types, and traces the origins of inconsistencies within genome-scale metabolic models.