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.
7 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.
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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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Documented deployment
Plan compute for AI drug discovery
Recursion documents DGX H100 systems and H100 GPUs in BioHive-2 for its AI drug discovery platform. The GPU is a component of the server, not a second required purchase.
1 · Inputs
Workload requirements and biological model/data specifications.
2 · Software & compute
Institutional cluster planning: networking, storage, power, cooling and software operations must be sized separately.
3 · Outputs
A compute architecture to evaluate; no ready-to-run discovery model is included.
4 · Laboratory handoff
Editorial next step: define the experimental feedback loop with laboratory scientists. No connection to a catalog instrument has been verified.
Licence & commercial use
Hardware purchase does not provide rights to models, biological data or proprietary discovery software.
Cost components
Hardware, networking, facilities, energy, support and engineering staff.
Evidence limitations
Deployment evidence demonstrates use, not a performance or cost guarantee for another research group.
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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.
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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 ↗