Ranomics
Yeast Display technical articles from the Ranomics scientific team

Yeast Display

Technical guides on yeast surface display: sizing the library, sorting by FACS and MACS, titrating display levels, and reading out hits by NGS.

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Articles 21 articles

Wet lab as an API for binder design agents

The Ranomics Platform API lets AI binder design agents submit candidates from RFdiffusion or ProteinMPNN runs directly to a real wet lab. Yeast display, mammalian display, or DMS. Enriched hits, NGS counts, and called binders return as structured JSON or signed webhooks.

Jun 8, 2026 Read →

Glycoprotein Engineering: Yeast Can't Do This, Mammalian Can

Glycoprotein engineering requires mammalian PTM machinery. When to skip yeast display and go straight to CHO/HEK293.

May 11, 2026 Read →

Yeast Display for Antibody Discovery: A CRO Methods Primer

Yeast display for antibody discovery: scaffold choices, library construction, MACS+FACS sorting, NGS hit calling, and developability triage.

May 11, 2026 Read →

Phage Display vs Yeast Display: When to Choose Which Platform

Phage display, yeast display, and mammalian display each fit different campaigns. A practical decision framework for choosing the right platform.

Apr 30, 2026 Read →

NNK vs NNS vs Trimer: Picking a Codon Scheme for a VHH Library

A practical comparison of NNK, NNS, NNN, and trimer codon schemes for VHH and scFv library design, covering stop codon frequency, amino acid coverage, S. cerevisiae codon bias, and when each scheme is the right choice for a yeast display campaign.

Apr 21, 2026 Read →

How Big a Yeast Display Library Do You Need for a 10 nM Binder?

A practical walkthrough of library size math for a 10 nM affinity target on yeast display: starting material, sort gate stringency, Poisson coverage for NGS, and the KD ladder across multiple rounds.

Apr 21, 2026 Read →

Binder Design on a Grant Budget: Scoping a Single-Target Campaign

What to prioritize, what to cut, and what actually determines cost when a PI or postdoc is running a single-target de novo binder design campaign on a defined budget.

Apr 20, 2026 Read →

Engineering pH-Dependent Antibodies on Yeast Surface Display: A 640-Clone Case Study

A technical walkthrough of a real pH-dependent antibody engineering campaign — 640-clone yeast display library, six FACS sorts, convergent hotspot residues, and quantitative enrichment-score ranking.

Apr 20, 2026 Read →

Closing the Loop: AI Protein Design Plus Display Screening

Most teams treat computational design and experimental screening as separate workflows. The programs that produce the best binders treat them as one coupled system.

Apr 14, 2026 Read →

The Two-Platform Approach: Using Yeast Display for Affinity and Mammalian Display for Developability

Don't choose between yeast display and mammalian display. This guide details a two-platform biologics discovery workflow, using yeast for affinity and mammalian display to screen for developability.

Nov 4, 2025 Read →

Troubleshooting Low Display Levels in Yeast and Mammalian Cells

Low or non-existent display levels are a common roadblock in yeast and mammalian display campaigns. A systematic diagnostic checklist for identifying and resolving the root cause.

Oct 2, 2025 Read →

Deconvoluting Polyclonal Hits: Strategies for Characterizing Enriched Library Pools

Your yeast display screen is finished, but choosing the most abundant clone from NGS data can lead to costly mistakes. A strategic framework for deconvoluting polyclonal hits using enrichment ratios and convergent evolution.

Sep 22, 2025 Read →

MACS for Library Pre-enrichment: When FACS Becomes the Bottleneck

Magnetic-activated cell sorting (MACS) pre-enriches naive yeast and mammalian display libraries with billions of variants — the throughput-first complement to FACS.

Sep 16, 2025 Read →

Beyond Antibodies: Using Surface Display to Engineer Enzymes and Receptors

While surface display is the go-to platform for antibody discovery, applications extend far beyond. This guide covers strategies for engineering enzymes and receptors using yeast and mammalian display.

Sep 10, 2025 Read →

The Numbers Game: Calculating Library Diversity with NGS

The success of any surface display campaign depends on library quality. A practical framework for NGS-based library validation covering diversity metrics, uniformity assessment, and sequencing workflows.

Sep 8, 2025 Read →

A Technical Guide to Sorting Strategies in Surface Display

In any yeast or mammalian surface display campaign, the flow cytometer is your primary selection tool. A guide to gating strategies, antigen titration, off-rate ranking, and counter-screening.

Sep 4, 2025 Read →

Titrating Display Levels for Reliable Affinity Data

Learn how to optimize display-level titration in yeast and mammalian display systems to obtain accurate affinity data and avoid avidity effects when determining Kd.

Aug 28, 2025 Read →

Protein Folding Optimization in Yeast Display: Engineering Better Expression Systems

Master protein folding optimization in yeast display systems with this guide covering signal peptide engineering, chaperone co-expression, ER retention strategies, and promoter optimization.

Aug 19, 2025 Read →

Avidity Artifacts in Yeast Display: Detecting False Positives

A practical guide to detecting and eliminating avidity artifacts in yeast display screening. Covers off-rate selection, soluble competition assays, display level titration, and FACS gating strategies with specific concentrations and timescales.

Aug 11, 2025 Read →

Library Size Limitations in Yeast Display: Maximizing Diversity

Discover proven strategies to maximize yeast display library diversity despite transformation limitations, including optimized protocols, Golden Gate cloning, and smart library design.

Aug 11, 2025 Read →

From Computational Protein Design to Validated Binders: What Actually Works

What separates successful AI protein design campaigns from failed ones? A practical breakdown of the computational and experimental steps required to go from generative models to validated binders.

Jun 15, 2025 Read →

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