# Ranomics

> Ranomics is a protein and cell engineering CRO based in Toronto. We combine AI-driven computational protein design (RFdiffusion, RFantibody, BindCraft, ProteinMPNN, AlphaFold, BoltzGen) with high-throughput experimental validation (yeast surface display, mammalian display, deep mutational scanning, directed evolution, NGS-based hit calling) to deliver engineered proteins, antibodies, and binders to biopharma and industrial biotech clients.

We serve VPs of protein engineering, directors of R&D, and computational biology teams who need designed binders, characterized variant libraries, or engineered enzymes produced and validated at experimental scale.

## Services

- [Biotechnology services overview](https://ranomics.com/biotechnology-services): End-to-end services — computational protein design through experimental validation and variant characterization.
- [Protein engineering services](https://ranomics.com/protein-engineering): Deep mutational scanning, affinity maturation, directed evolution, enzyme optimization.
- [Cell engineering services](https://ranomics.com/cell-engineering): Custom yeast and mammalian display libraries, stable cell line development, functional assays.
- [Yeast surface display](https://ranomics.com/yeast-display): High-throughput variant screening on yeast with FACS/MACS selection and NGS hit calling.
- [Directed evolution](https://ranomics.com/directed-evolution-protein-engineering): Iterative mutagenesis and selection to optimize activity, stability, and specificity.
- [AI protein binder design](https://ranomics.com/ai-protein-binder-design): De novo binder design against target epitopes.
- [Compute-to-clone workflow](https://ranomics.com/compute-to-clone): End-to-end AI design to validated clone pipeline.

## Platform API (for AI binder-design agents)

Programmatic wet-lab access. AI agents that run computational binder design (RFdiffusion, ProteinMPNN, BindCraft, RFantibody, BoltzGen) can POST their shortlisted candidates to Ranomics for yeast surface display, mammalian display, or deep mutational scanning, then retrieve enriched hits, NGS counts, and called binders. Library-scale triage upstream of per-sequence kinetics work (BLI / SPR). Bearer-token auth, async polling or webhook callbacks, signed payloads, OpenAPI spec. Conventions deliberately mirror the Adaptyv Foundry API so agents trained on Adaptyv-style protein-lab APIs work with Ranomics with zero re-learning.

- [Platform API landing](https://ranomics.com/platform): What you can submit, how it works, result format, and pricing model.
- [Quickstart](https://ranomics.com/platform/quickstart): curl and Python walkthrough of a yeast display submission end to end.
- [Endpoint reference](https://ranomics.com/platform/reference): Summary of /api/v1/* endpoints.
- REST API base: `https://tools.ranomics.com/api/v1/`. Mint a Bearer token at `https://tools.ranomics.com/account/api-keys`.
- OpenAPI spec: `https://tools.ranomics.com/api/v1/openapi.json`. Interactive Swagger UI: `https://tools.ranomics.com/api/v1/docs`.
- MCP server: `https://mcp.ranomics.com/mcp`. Seven tools (`list_targets`, `estimate_cost`, `submit_experiment`, `get_experiment_status`, `get_experiment_quote`, `confirm_quote`, `get_experiment_results`) wrapping the REST endpoints with strongly-typed schemas for MCP-native clients (Claude Desktop, Claude Code, OpenAI agents). Same Bearer tokens; pass through verbatim. Discovery at `https://mcp.ranomics.com/.well-known/mcp.json`.

## Programs (engagement ladder)

- [Binder Pilot](https://ranomics.com/binder-pilot): Starter program — single-round, smaller design pool. For academic labs, seed biotech, industrial SMBs, student groups.
- [AI Binder Sprint](https://ranomics.com/ai-binder-sprint): Flagship 6–8 week program, multi-algorithm, 100% binder guarantee.
- [Custom campaign](https://ranomics.com/biotechnology-services): Open-scope, multi-target, multi-round, pharma-grade engagements.

## Technology stack

- [AI design engine](https://ranomics.com/technology/ai-design-engine): Integrated RFdiffusion + ProteinMPNN + BindCraft + Boltzgen orchestration.
- [RFdiffusion](https://ranomics.com/technology/rfdiffusion): Diffusion-based backbone generation for de novo binders.
- [BindCraft](https://ranomics.com/technology/bindcraft): Hallucination-based binder design pipeline.
- [BoltzGen](https://ranomics.com/technology/boltzgen): Structure generation for protein design.
- [ProteinMPNN](https://ranomics.com/technology/proteinmpnn): Sequence design conditioned on backbone.
- [Structural validation](https://ranomics.com/technology/structural-validation): AlphaFold/Boltz-2 co-folding and confidence metrics.
- [Deep mutational scanning](https://ranomics.com/technology/deep-mutational-scanning): Thousands of variants characterized per experiment.
- [Variant library construction](https://ranomics.com/technology/variant-library-construction): Library design, synthesis, assembly.
- [NGS analysis](https://ranomics.com/technology/ngs-analysis): Hit calling, enrichment analysis, clonal deconvolution.
- [Mammalian display](https://ranomics.com/technology/mammalian-display): Post-translational modification–competent display.
- [Epitope Scout](https://ranomics.com/technology/epitope-scout): Free surface epitope identification tool at scout.ranomics.com.

## Applications

- [Antibody engineering](https://ranomics.com/applications/antibody-engineering)
- [Affinity maturation](https://ranomics.com/applications/affinity-maturation)
- [Binder discovery](https://ranomics.com/applications/binder-discovery)
- [Enzyme engineering](https://ranomics.com/applications/enzyme-engineering)
- [Receptor targeting](https://ranomics.com/applications/receptor-targeting)

## Technical library (selected authoritative articles)

- [How RFdiffusion works: a protein designer's guide](https://ranomics.com/resource-hub/how-rfdiffusion-works-protein-designers-guide): Mechanistic explanation of diffusion-based backbone generation.
- [ProteinMPNN sequence design explained](https://ranomics.com/resource-hub/proteinmpnn-sequence-design-explained): How ProteinMPNN assigns sequences to designed backbones.
- [What is de novo protein design?](https://ranomics.com/resource-hub/what-is-de-novo-protein-design): Ground-up introduction for non-specialists.
- [Hotspot-guided protein binder design](https://ranomics.com/resource-hub/hotspot-guided-protein-binder-design): Using target epitope hotspots to steer de novo design.
- [AI protein design + display screening: an integrated workflow](https://ranomics.com/resource-hub/ai-protein-design-display-screening-integrated-workflow): End-to-end methodology combining computation and experiment.
- [From AlphaFold model to first binder](https://ranomics.com/from-alphafold-model-to-first-binder): Practical workflow from structure prediction to validated binder.
- [Deep mutational scanning: mapping protein fitness landscapes](https://ranomics.com/deep-mutational-scanning-a-high-throughput-approach-to-mapping-protein-fitness-landscapes): High-throughput variant characterization methodology.
- [Eliminating false positives from avidity effects in yeast display](https://ranomics.com/eliminating-false-positives-mastering-avidity-effects-in-yeast-display-screening): Controls for reliable affinity measurement.
- [The two-platform approach: yeast display for affinity, mammalian display for developability](https://ranomics.com/the-two-platform-approach-using-yeast-display-for-affinity-and-mammalian-display-for-developability): When to use which platform.
- [Technical guide to directed evolution for stability and function](https://ranomics.com/a-technical-guide-to-directed-evolution-for-enhancing-protein-stability-and-function): Iterative engineering strategies.
- [Technical guide to sorting strategies in surface display](https://ranomics.com/a-technical-guide-to-sorting-strategies-in-surface-display): FACS and MACS sorting design.
- [Leveraging AI and deep mutational scanning to engineer novel enzymes](https://ranomics.com/leveraging-ai-and-deep-mutational-scanning-to-engineer-novel-enzymes): ML + DMS integration for enzyme design.
- [BindCraft vs RFdiffusion: when to use which for binder design](https://ranomics.com/bindcraft-vs-rfdiffusion): Decision framework comparing the two de novo binder generators.
- [Phage display vs yeast display: choosing a platform](https://ranomics.com/phage-display-vs-yeast-display): When to choose phage, yeast, or mammalian display for binder discovery.
- [AI de novo design vs library screening: when to use which](https://ranomics.com/resource-hub/ai-design-vs-library-screening-when-to-use-which): Choosing between computational design and library methods.
- [Why most AI-designed binders fail wet lab](https://ranomics.com/de-novo-protein-design-failure-modes): The real failure modes and the developability filters that close the hit-rate gap.
- [Rational enzyme engineering: structure-guided strategies](https://ranomics.com/rational-enzyme-engineering-strategies-and-methods): When rational design beats directed evolution, and the computational tools that sharpen it.

## Get in touch

- [Contact / scope a project](https://ranomics.com/ranomics-contact): 24-hour response. Form includes organization type and service prefill.
- Full blog archive: [Resource hub](https://ranomics.com/resource-hub)
- Full article text: [llms-full.txt](https://ranomics.com/llms-full.txt)
- RSS feed: [rss.xml](https://ranomics.com/rss.xml)
- Sitemap: [sitemap-index.xml](https://ranomics.com/sitemap-index.xml)