VitaminP uses paired H&E-mIF data to train a model that transfers molecular boundary information, enabling accurate whole-cell segmentation directly from routine H&E histology across 34 cancer types.
Predicting transcriptional outcomes of novel multigene perturba- tions with GEARS
5 Pith papers cite this work. Polarity classification is still indexing.
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Shesha quantifies directional coherence of single-cell CRISPR responses, correlates strongly with effect magnitude, distinguishes pleiotropic from lineage-specific regulators, and predicts chaperone activation after magnitude correction.
Radiogenomic models using MRI features from multiple public datasets predicted the M0 macrophage immune signature in IDH-wildtype glioblastoma with mean balanced accuracy 0.67 and precision 0.89 on held-out cohorts.
MicroDiffuse3D is a foundation model that restores 3D microscopy images under sparse super-resolution, joint degradation, and low-SNR denoising, reporting 10.58% segmentation and 15.59% line-profile gains over baselines.
CovAngelo implements a QM/QM/MM embedding model using quantum-information metrics to compute reaction energy profiles and barriers for covalent drug binding at lower cost than conventional methods, demonstrated on zanubrutinib to BTK.
citing papers explorer
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VitaminP: cross-modal learning enables whole-cell segmentation from routine histology
VitaminP uses paired H&E-mIF data to train a model that transfers molecular boundary information, enabling accurate whole-cell segmentation directly from routine H&E histology across 34 cancer types.
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Geometric coherence of single-cell CRISPR perturbations reveals regulatory architecture and predicts cellular stress
Shesha quantifies directional coherence of single-cell CRISPR responses, correlates strongly with effect magnitude, distinguishes pleiotropic from lineage-specific regulators, and predicts chaperone activation after magnitude correction.
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Predictive Radiomics for Evaluation of Cancer Immune SignaturE in Glioblastoma: the PRECISE-GBM study
Radiogenomic models using MRI features from multiple public datasets predicted the M0 macrophage immune signature in IDH-wildtype glioblastoma with mean balanced accuracy 0.67 and precision 0.89 on held-out cohorts.
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MicroDiffuse3D: A Foundation Model for 3D Microscopy Imaging Restoration
MicroDiffuse3D is a foundation model that restores 3D microscopy images under sparse super-resolution, joint degradation, and low-SNR denoising, reporting 10.58% segmentation and 15.59% line-profile gains over baselines.
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CovAngelo: A hybrid quantum-classical computing platform for accurate and scalable drug discovery
CovAngelo implements a QM/QM/MM embedding model using quantum-information metrics to compute reaction energy profiles and barriers for covalent drug binding at lower cost than conventional methods, demonstrated on zanubrutinib to BTK.