perturbation screen

Predicting differentially expressed genes and expression shifts per condition from database embeddings plus per-gene evidence, PIE reaches 1.2–3.2 times the best baseline's AUPRC on unseen contexts, perturbations and datasets.

The paper develops a framework combining perturbation screens and transfer learning to reconstruct signaling histories in cells and optimize differentiation protocols.

A set-aware latent transport model predicts treated cell populations from unpaired controls, keeps perturbation-specific signal in CRISPR, drug and cytokine data, and guided a cytokine choice tested in three donors.

Across 13 single-cell foundation models and 94 datasets, PCA and established methods usually match or beat them; pretrained embeddings help mainly with scarce labels, rare cells and open-set detection.

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.

Genome-scale CRISPRi perturb-seq in 22 million primary human CD4+ T cells maps stimulation-specific regulators and links perturbation signatures to T cell states and autoimmune genetics.

A >50,000-element viral smORF library screened by growth, MHC-I, ER stress, Perturb-seq and mass spectrometry yields >2,000 active microproteins and shows EBV BNLF2b inhibits PKA by mimicry.

DRiF-Seq, a sequencing-optimized RNAi platform with a posteriori noise estimation, quantifies clone-resolved fitness genome-wide in pleomorphic Trypanosoma brucei; over half of core genes carry fitness costs.

OCellus is a language model that addresses limitations in single-cell, spatial, and perturbation biology by integrating natural-language reasoning across multiple tasks.

BrainBridge integrates single-cell transcriptomic data with phenotypes to model brain biology, prioritizing genes and cell types linked to Alzheimer's, aging, and sex differences.

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.

MOFA, a sparse Bayesian factor model with mixed likelihoods, separates shared from modality-specific multi-omic variation, recovering IGHV, trisomy 12 and oxidative-stress axes in 200 leukaemia samples.