3 papers
cs.AI2026
VCLMU: Mechanism-Centric Virtual Cell World Modeling for Perturbation Response
Yuwei Miao, Azim Dehghani Amirabad, Scott Oloff +3
Predicting cellular responses to genetic perturbations is a central capability for virtual cells and a key step toward computational modeling of biological interventions. Most exis…
cs.CV2026
PaSTel: Anchoring Histology in Spatial Transcriptomics via Multi-Scale Hierarchical Bio-Prior Contrastive Pretraining
Azim Dehghani Amirabad, Junchao Zhu, Pushpak Pati +3
Spatial transcriptomics (ST) links tissue morphology with molecular programs, motivating multimodal pretraining methods that align histology images with gene expression. However, e…
q-bio.GN2025
Multimodal Modeling of CRISPR-Cas12 Activity Using Foundation Models and Chromatin Accessibility Data
Azim Dehghani Amirabad, Yanfei Zhang, Artem Moskalev +5
Predicting guide RNA (gRNA) activity is critical for effective CRISPR-Cas12 genome editing but remains challenging due to limited data, variation across protospacer adjacent motifs…