Article

pertTF: context-aware AI modeling for genome-scale and cross-system perturbation prediction

2026-03-16

Abstract excerpt

Predicting genetic perturbation responses at a single-cell level is central to building models for cell state and disease. However, existing approaches are limited on predicting phenotypic outcomes beyond expression changes and generalizing predictions across genome-scale perturbations in biologically relevant contexts. Here we introduce pertTF, a transformer-based single-cell genetic perturbation model. pertTF wa...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: d5dc4503-0b3b-5e8c-9a89-d8eddf698e02
DOI: 10.64898/2026.03.12.711379

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

pertTF: context-aware AI modeling for genome-scale and cross-system perturbation predictionDOI 10.64898/2026.03.12.711379Read

AttentionPert: Accurately Modeling Multiplexed Genetic Perturbations with Multi-scale EffectsSemantic proximity Read

Multimodal foundation model predicts zero-shot functional perturbations and cell fate dynamicsSemantic proximity Read

Tabular Foundation Models Are Competitive Cellular Perturbation Predictors Across Biological ScalesSemantic proximity Read

Benchmarking AI Models for <i>In Silico</i> Gene Perturbation of CellsSemantic proximity Read

Stack: In-Context Learning of Single-Cell BiologySemantic proximity Read

X-Cell: Scaling Causal Perturbation Prediction Across Diverse Cellular Contexts via Diffusion Language ModelsSemantic proximity Read

Benchmarking a foundational cell model for post-perturbation RNAseq predictionSemantic proximity Read

Inference of gene regulatory networks using time-series single-cell RNA-seq data with CRISPR perturbationsSemantic proximity Read

Predicting how perturbations reshape cellular trajectories with PerturbGenSemantic proximity Read

Reversing pathological cell states: the road less travelled can extend the therapeutic horizon.Semantic proximity Read

Scalable and universal prediction of cellular phenotypes enables in silico experimentsSemantic proximity Read

Global cell-state and gene-program representations reveal conserved and context-specific perturbation responses of cellsSemantic proximity Read