Jeffrey Joseph Ishizuka

Perturbational single-cell profiling of patient tumors defines lineage- and context-specific programs of innate immune resistance

The paper uses patient tumor samples to identify lineage- and context-specific mechanisms of innate immune resistance through perturbational single-cell RNA sequencing.

Scaling Large Language Models for Next-Generation Single-Cell Analysis

This paper scales large language models for single-cell analysis, improving predictive and generative capabilities and enabling biological discovery through virtual screening.

Clinico-genomic features predict distinct metastatic phenotypes in cutaneous melanoma

This study identifies distinct metastatic phenotypes in cutaneous melanoma using clinico-genomic data and machine learning, linking specific mutations and clinical factors to organ-specific metastasis.

Causal identification of single-cell experimental perturbation effects with CINEMA-OT

CINEMA-OT identifies causal effects of single-cell perturbations by separating confounding variation, outperforming existing methods on simulated and real datasets.