Aidan F. Winters

Predicting cellular responses to perturbation across diverse contexts with STATE

State, a set-based transformer trained on over 100 million perturbed cells, predicts perturbation responses in new cellular contexts better than mean, linear and deep learning baselines.

Scalable probe-based single-cell transcriptional profiling for virtual cell perturbation mapping and synthetic biology phenotyping

ProPer-seq is a cost-effective, barcode-free single-cell perturbation profiling method that enables scalable analysis of synthetic biology perturbations and reveals transcriptional control principles.

Tahoe-100M: A Giga-Scale Single-Cell Perturbation Atlas for Context-Dependent Gene Function and Cellular Modeling

A 100-million-cell atlas: 50 cancer lines pooled as spheroid villages, treated with 379 drugs at several doses, profiled by combinatorial-barcoding scRNA-seq and embedded with a 10-dimensional scVI model.

A systematic search for RNA structural switches across the human transcriptome

The paper identifies 245 putative RNA structural switches in the human transcriptome using a computational and experimental approach, validates one with DMS-MaPseq and cryo-EM, and shows its regulation by trans factors and nonsense-mediated decay.

SCITO-seq: single-cell combinatorial indexed cytometry sequencing

SCITO-seq enables cost-effective profiling of over 10^5 cells using combinatorial indexing with dsc-seq, demonstrating feasibility in mixed cell lines and human lymphocytes.