Danny Reidenbach

Latent generative search unlocks de novo design of untapped biomolecular interactions at scale

Reward-guided inference-time search over the Proteína-Complexa sequence-structure codesign model yields validated binders across 127 targets, kinases and a free carbohydrate, with codesigned sequences outperforming ProteinMPNN redesign.

Advancing Protein Ensemble Predictions Across the Order-Disorder Continuum

The paper introduces a benchmark for evaluating protein ensemble generators across ordered and disordered proteins and presents a new model that improves performance on disordered regions.

PeakVI: A Deep Generative Model for Single Cell Chromatin Accessibility Analysis

PeakVI is a deep generative model for scATAC-seq data analysis that corrects batch effects, preserves biological heterogeneity, and identifies differential accessibility.

GEPSi: A Python Library to Simulate GWAS Phenotype Data

GEPSi simulates GWAS phenotype data with biological complexity to benchmark genetic analysis methods.