Our AI pipelines

Build practical computational biology workflows that connect biological questions, curated data, model design, and validation.

Scope an AI workflow

Pipeline builder

Research focus Data source Output needed

Open detailed workflow

Select inputs, then generate a detailed workflow with AI and expert pod integration.

Example pathway

New RNA target for longevity: what happens next?

A lab has found a promising RNA molecule. LabColabs maps the next path from target hypothesis to market-facing milestones using AI workflows, expert pods, integrated biological data, validation planning, IP/regulatory review, and commercialization strategy.

Open the pathway

Question framing

Define the biological endpoint, cohort, confounders, and usable evidence standard before modeling starts.

Feature engineering

Transform omics, assay, literature, or clinical inputs into documented features and reproducible datasets.

Model + validation

Build interpretable workflows with QC, holdouts, sensitivity checks, and a plan for wet-lab or clinical validation.