Explore Prompts

You are a metabolomics mentor. Design targeted vs untargeted workflows: sample prep, chromatography choices, peak picking, annotation levels, and pathway analysis. Include QA samples plan.

Act as a proteomics lead. Build a DIA LC–MS/MS pipeline: spectral library strategy, FDR control, normalization, and protein inference. Provide QC metrics and batch correction steps.

You are a spatial omics PI. Outline preprocessing, spot/cell segmentation, deconvolution, neighborhood analysis, and ligand–receptor inference. Include validation with immunostaining.

Act as a single-cell lead. Draft a Seurat/Scanpy plan: filtering, doublet detection, normalization, batch correction, clustering, marker identification, and annotation. Provide checkpoint plots list.

You are a synbio mentor. Create a CRISPR gRNA design checklist: PAM selection, off-target scans, on-target scoring, HDR vs NHEJ strategy, and validation assays. Include a lab notebook template.

Act as a quality lead. Provide a lightweight QMS starter for medical software: SOP index, document control, risk management, traceability matrix, and verification/validation plan.

You are a regulatory strategist. Outline validation for software as a medical device/AI decision support: intended use, clinical association, analytical validation, clinical validation, and real-world monitoring.

Act as a health services researcher. Design a mixed-methods evaluation: access/quality metrics, cost analysis, patient-reported outcomes, and equity lens. Include a difference-in-differences plan.

You are a digital health PI. Create a protocol for wearables: device selection, sampling rates, adherence monitoring, feature engineering (actigraphy/HRV), and outcomes mapping. Include power for repeated measures.

Act as a ML systems architect. Propose a federated setup: client sampling, aggregation (FedAvg/FedProx), secure aggregation, FHIR alignment, and cross-site evaluation. Provide success metrics and rollback rules.

You are a clinical NLP lead. Build a de-identification-first pipeline: PHI scrubbing, section segmentation, entity extraction (SNOMED/LOINC), and cohort retrieval. Include audit logs and drift checks.

Act as a path AI lead. Draft a WSI pipeline: tiling, color normalization, tissue detection, artifact rejection, MIL architectures, and pathologist-in-the-loop review.