Bingobin/DRUGseq-PerturbFormer: DPF v1.0.1
Abstract
This release provides the version of the DRUGseq-PerturbFormer framework used in the analyses reported in the accompanying manuscript. The code implements a deep learning–based model for predicting transcriptional responses to metabolite perturbations from DRUG-seq data. This release corresponds to the version used for all analyses and results presented in the study.
Fields of Study & Subjects
Computational Drug Discovery Methods
Single-cell and spatial transcriptomics
Gene Regulatory Network Analysis
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 16 January 2026