Richard W. Shuai

Isolation of structural constraints by ensemble-conditioned protein sequence design

This paper introduces Caliby, a sequence design method that conditions on structural ensembles to improve designability while reducing native sequence recovery.

Conditional Protein Structure Generation with Protpardelle-1c

Protpardelle-1c is a protein structure generative model that improves motif scaffolding and multi-chain complex generation, achieving higher scores and faster sampling than existing models.

Sidechain conditioning and modeling for full-atom protein sequence design with FAMPNN

This paper introduces FAMPNN, a method for protein sequence design that explicitly models both amino acid identity and sidechain conformation, achieving state-of-the-art results in sidechain packing and practical design applications.

Variants in tubule epithelial regulatory elements mediate most heritable differences in human kidney function

This paper identifies genetic variants in tubule epithelial regulatory elements that explain most heritable differences in human kidney function using GWAS, scATAC-seq, and functional assays.

Current genomic deep learning models display decreased performance in cell type specific accessible regions

The paper evaluates deep learning models for predicting chromatin accessibility and finds reduced performance in cell type-specific regions, suggesting strategies to improve accuracy.

Characterizing uncertainty in predictions of genomic sequence-to-activity models

This study examines uncertainty in genomic sequence-to-activity model predictions by analyzing consistency across different sequence types and identifies areas where models perform poorly.

Personal transcriptome variation is poorly explained by current genomic deep learning models

This study evaluates genomic deep learning models' ability to explain individual expression variation and finds limited performance.

Unlocking de novo antibody design with generative artificial intelligence

Deep generative models combined with high-throughput screening design de novo anti-HER2 antibodies without further optimization, yielding nanomolar binders functionally comparable or superior to trastuzumab.