FROM RESEARCH QUESTION TO TOOLS
Build your research workflow
Connect software, computing and laboratory steps using documented evidence. A workflow is a planning guide, not a validated experimental protocol.
Research workflow suitability and Decision Passport
The previous fixed-template workflow scorer cannot establish comparative scientific suitability. For a task-specific assessment, enter the biological objective, the actual sample/data modalities and method constraints in the offline Decision Lab. Select the reviewed method deliberately and compare it against a mandatory non-AI baseline.
Open scientific Decision LabHistorical workflow templates are examples, not validated executable pipelines, clinical decisions or ranked model recommendations.
CORE BIOAI WORKFLOW PILLARS
Industry-Standard Computational Biology Blueprints
🧬Protein Structure & Binder Design
Benchmark AlphaFold 3, RFdiffusion, Chai-1, and ProteinMPNN. Compare open weights vs. cloud APIs with curated Academic and Startup stacks.
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💊Small-Molecule Docking & Design
Benchmark DiffDock, EquiBind, GNINA, and Chemistry42 across docking accuracy and screening throughput.
Explore Workflow Blueprint →
🦠Single-Cell & Spatial Omics Analysis
Compare scvi-tools, Scanpy, Seurat, scGPT, and cell2location for cell atlasing and perturbation modeling.
Explore Workflow Blueprint →
6 documented paths · Evidence and planning notes recorded September 2026. Commercial eligibility has not been independently confirmed for these complete workflows.
Provider-tested configuration
Predict biomolecular structures
AlphaFold 3 documentation lists a single H100 80 GB as an officially supported inference configuration. Other H100 variants are not established by this evidence.
1 · Inputs
Biomolecular sequences and supported molecular inputs, with sequence-search preparation.
2 · Software & compute
H100 80 GB; CPU/RAM and sequence databases are also required. Larger inputs can require configuration changes.
3 · Outputs
Predicted structures for scientific review.
4 · Laboratory handoff
Editorial next step: select an appropriate structural or functional validation assay with the research team. No direct instrument integration has been verified.
Licence & commercial use
Code and model parameters have separate terms. Parameter access must be obtained from the provider; commercial eligibility is not established here.
Cost components
GPU access, CPU preparation, sequence storage and researcher time; no live price estimate.
Evidence limitations
Hardware support is not evidence of accuracy for a particular biological target. No local benchmark was run.
Inspect original evidence ↗
Provider implementation example
Run protein-folding workflows in the cloud
AWS documents AlphaFold2 and OpenFold workflows on SageMaker. This evidence does not establish AlphaFold 3 compatibility.
1 · Inputs
Protein sequences and the chosen workflow's reference data.
2 · Software & compute
Workflow-specific cloud instances, storage and orchestration; verify current instance availability and dependencies.
3 · Outputs
Structure predictions and tracked experiments.
4 · Laboratory handoff
Editorial next step: choose experimental validation based on the biological question. No automatic laboratory handoff is documented here.
Licence & commercial use
AWS service terms and each model/data licence must be evaluated separately.
Cost components
Instance runtime, storage, data transfer and idle resources; confirm regional prices.
Evidence limitations
Historical implementation example; not a guarantee that the original deployment instructions still run unchanged.
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Manufacturer-listed research
Connect cellular imaging to machine-learning analysis
Revvity lists research combining Opera Phenix imaging with machine learning. AI analysis is a workflow component, not assumed to be included in every instrument configuration.
1 · Inputs
Prepared biological samples and an imaging assay.
2 · Software & compute
Analysis workstation or server requirements depend on the selected pipeline and image volume; not yet verified.
3 · Outputs
Cellular images and analysis-dependent measurements.
4 · Laboratory handoff
Imaging is the laboratory step. Confirm assay design, controls, sample formats and export compatibility before linking an analysis tool.
Licence & commercial use
Instrument, analysis software and model licences require separate confirmation.
Cost components
Instrument quotation, maintenance, consumables, analysis software and compute.
Evidence limitations
Publication-list evidence, not an independently reproduced benchmark or verified plug-and-play integration.
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Project documentation; editorial evaluation plan
Evaluate cell segmentation
Compare these alternative analysis tools on the same images; no cross-tool interoperability is asserted.
1 · Inputs
Microscopy images with representative expert annotations
2 · Software & compute
Select the release and dataset size before sizing CPU, GPU, RAM and storage; no hardware configuration verified here.
3 · Outputs
Segmentation masks or workflow-specific classifications
4 · Laboratory handoff
Editorial next step: review results against independent annotations, truth sets or relevant experiments. No automatic laboratory integration is established.
Licence & commercial use
Confirm the selected code, model and data terms separately.
Cost components
Compute, storage, annotation and researcher time; no current price estimate.
Evidence limitations
Tools are not locally benchmarked; this path describes an evaluation plan and does not assert clinical validity or superiority.
Inspect original evidence ↗
Project documentation; editorial evaluation plan
Evaluate single-cell representations
These are alternative research approaches. Batch effects and held-out donor evaluation must be considered; a direct pipeline between them is not verified.
1 · Inputs
Quality-controlled single-cell expression data
2 · Software & compute
Select the release and dataset size before sizing CPU, GPU, RAM and storage; no hardware configuration verified here.
3 · Outputs
Model-specific embeddings or downstream predictions
4 · Laboratory handoff
Editorial next step: review results against independent annotations, truth sets or relevant experiments. No automatic laboratory integration is established.
Licence & commercial use
Confirm the selected code, model and data terms separately.
Cost components
Compute, storage, annotation and researcher time; no current price estimate.
Evidence limitations
Tools are not locally benchmarked; this path describes an evaluation plan and does not assert clinical validity or superiority.
Inspect original evidence ↗
Project documentation; editorial evaluation plan
Evaluate a variant-calling pipeline
Choose the sequencing-platform model and compare to appropriate reference truth data; this is not clinical interpretation.
1 · Inputs
Aligned reads, reference genome and platform-matched model
2 · Software & compute
Select the release and dataset size before sizing CPU, GPU, RAM and storage; no hardware configuration verified here.
3 · Outputs
Genetic variant calls
4 · Laboratory handoff
Editorial next step: review results against independent annotations, truth sets or relevant experiments. No automatic laboratory integration is established.
Licence & commercial use
Confirm the selected code, model and data terms separately.
Cost components
Compute, storage, annotation and researcher time; no current price estimate.
Evidence limitations
Tools are not locally benchmarked; this path describes an evaluation plan and does not assert clinical validity or superiority.
Inspect original evidence ↗
