11 papers
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…
BioBO: Biology-informed Bayesian Optimization for Perturbation Design
Yanke Li, Tianyu Cui, Tommaso Mansi +2
Efficient design of genomic perturbation experiments is crucial for accelerating drug discovery and therapeutic target identification, yet exhaustive perturbation of the human geno…
TRIDENT: Tri-Modal Molecular Representation Learning with Taxonomic Annotations and Local Correspondence
Feng Jiang, Mangal Prakash, Hehuan Ma +6
Molecular property prediction aims to learn representations that map chemical structures to functional properties. While multimodal learning has emerged as a powerful paradigm to l…
HyperHELM: Hyperbolic Hierarchy Encoding for mRNA Language Modeling
Max van Spengler, Artem Moskalev, Tommaso Mansi +2
Language models are increasingly applied to biological sequences like proteins and mRNA, yet their default Euclidean geometry may mismatch the hierarchical structures inherent to b…
GRAM-DTI: adaptive multimodal representation learning for drug target interaction prediction
Feng Jiang, Amina Mollaysa, Hehuan Ma +4
Drug target interaction (DTI) prediction is a cornerstone of computational drug discovery, enabling rational design, repurposing, and mechanistic insights. While deep learning has…
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…