Research Notebook
Research Notebook
Research taught me to treat reproducibility as infrastructure.
100+global researchersusing the platform
8biomarker candidatesfrom multi-omics analyses
3manuscripts in reviewlead-author, under review
- Biological samplesRaw specimens, assays, observations
- IngestionCollect & record data at scale
- ValidationQuality checks, controls, provenance
- ModelsAnalyze, learn, test
- Reproducible artifactsNotebooks, code, data packages, reports
- Production patternsPipelines, APIs, platforms, monitoring
- TCGA / PCAWG raw
- Harmonize
- QC (K-Means / DBSCAN)
- Feature select (SVM-RFE)
- Model (Random Forest)
- Validated biomarkers
- Manuscript figures
- PeopleResearchers, techs
- ToolsNextflow · R · Python
- EnvironmentsConda · Docker · HPC
- StorageHPC scratch · S3 · checksums
- TimeTimestamps, versions
| Field | Type | Description | Notes |
|---|---|---|---|
| study_id | string | Unique study identifier | PK |
| sample_id | string | Sample identifier | indexed |
| modality | enum | e.g., DNA, ATAC, Proteomics | controlled |
| batch_id | string | Acquisition batch | traceable |
| instrument | string | Instrument / platform | versioned |
| raw_path | string | Raw data location | immutable |
| qc_metrics | json | Quality control metrics | validated |
| created_at | timestamp | Ingestion timestamp | UTC |
- Version control for code & configs
- Immutable raw data storage
- Documented protocols & parameters
- Deterministic environments
- Automated validation & QC
- Re-runnable pipelines (idempotent)
- Provenance captured end-to-end
- Shareable artifacts & reports
- Peer review & independent verification
| Research | Engineering |
|---|---|
| Reproducibility | Idempotency |
| Provenance | Lineage |
| Experimental controls | Validation |
| Peer review | Observability |