[ Platform ]
End-to-end metabolic intelligence infrastructure.
From raw multi-omics data to validated transducer hypotheses, every layer of the Meteor platform is engineered for metabolic discovery.
[ Architecture ]
Six layers. One pipeline.
Each layer of the platform is modular, auditable, and designed to operate at production scale.
01
Data Ingestion
- Multi-omics upload (LCMS, targeted, untargeted, lipidomics)
- Cloud storage connectors (S3, GCS, Azure Blob)
- Automated format detection and schema validation
- Batch import with parallel processing
02
Quality Control
- Six-checkpoint QC pipeline per dataset
- Outlier detection with configurable thresholds
- Batch correction (ComBat, limma)
- Normalization quality scoring
03
Compute Engine
- GPU-accelerated dimensionality reduction
- Distributed analysis across multi-node clusters
- Adaptive resource allocation based on dataset size
- Sub-15-minute median run time for standard cohorts
04
Analysis Models
- Phenotype stratification via UMAP / PCA / t-SNE
- Bioenergetic axis mapping with flux balance integration
- Transducer hypothesis ranking using Bayesian enrichment
- Metabolic gene signature analysis (GSEA, ssGSEA, VISION)
05
Visualization & Reporting
- Interactive phenotype maps with cluster annotations
- Signature similarity heatmaps
- Driver ranking with confidence intervals
- Auto-generated PDF reports with citation management
06
Integration & API
- RESTful API with OpenAPI 3.1 specification
- Webhook notifications for run completion
- Programmatic run submission and result retrieval
- SSO integration (SAML 2.0, OIDC)
12,000+
Metabolites profiled
<15 min
Median run time
99.1%
QC accuracy
6
Validation checkpoints
See the platform in action.
Request a guided walkthrough with our science team.