Drug toxicity prediction is an important step in ensuring patient safety during drug design
studies. While traditional preclinical studies have historically relied on animal models to …

Morphological profiling is a valuable tool in phenotypic drug discovery. The advent of high-
throughput automated imaging has enabled the capturing of a wide range of morphological …

Image-based profiling techniques have become increasingly popular over the past decade
for their applications in target identification, mechanism-of-action inference, and assay …

Molecular representation learning (MRL) is essential in certain applications including drug
discovery and life science. Despite advancements in multiview and multimodal learning in …

Predicting molecular impact on cellular function is a core challenge in therapeutic design.
Phenomic experiments, designed to capture cellular morphology, utilize microscopy based …

With the surge in available data from various modalities, there is a growing need to bridge
the gap between different data types. In this work, we introduce a novel approach to learn …

Predicting single-cell transcriptomes following perturbation is crucial for understanding gene
regulation and guiding drug discovery. Yet, the complexity of perturbation effects pose …

With the surge in available data from various modalities, there is a growing need to bridge
the gap between different data types. In this work, we introduce a novel approach to learn …

The advent of high-throughput automated imaging technology has enabled us to capture
various morphological features of single cells under different perturbations at single-cell …

Predicting molecular impact on cellular function is a core challenge in therapeutic design.
Phenomic experiments, designed to capture cellular morphology, utilize microscopy based …