scCycleMol adds a learnable circular cell-cycle head with closed-loop supervision from predicted treated expression, yielding higher r-squared on SciPlex3 gene predictions and improved phase accuracy versus ChemCPA baselines.
Predicting transcriptional responses to novel chemical perturbations using deep generative model for drug discovery.Nature Communications, 15(1):9256, 2024
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Chem2Gen-Bench is a new benchmark and evaluation framework for measuring alignment between chemical and genetic perturbation responses in matched cell-target contexts using retrieval, similarity, and embedding comparisons.
citing papers explorer
-
Modeling Cell-Cycle-Aware Single-Cell Drug Perturbation Responses
scCycleMol adds a learnable circular cell-cycle head with closed-loop supervision from predicted treated expression, yielding higher r-squared on SciPlex3 gene predictions and improved phase accuracy versus ChemCPA baselines.
-
Chem2Gen-Bench: Benchmarking Chemical-to-Genetic Translation in Perturbation Response Space
Chem2Gen-Bench is a new benchmark and evaluation framework for measuring alignment between chemical and genetic perturbation responses in matched cell-target contexts using retrieval, similarity, and embedding comparisons.