Emily K. Makowski

Property Enhancer - a data efficient multi-objective approach for functional antibody optimization

Property Enhancer optimizes antibody properties using a data-efficient framework, achieving significant affinity gains in both in silico and in vitro tests.

Lab-in-the-loop therapeutic antibody design with deep learning

This paper introduces a machine learning framework for therapeutic antibody design that integrates computational methods with experimental validation, resulting in significantly improved binding affinity for multiple targets.

Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data

The paper introduces PSERM scoring to predict antibody variant properties from deep sequencing data, showing it outperforms traditional methods in reproducibility and correlation with experimental measurements.