Takamasa Kudo

The paper introduces CellMAPP and CHART to analyze multiplexed antibody imaging data, revealing modular morphological programs in response to genetic perturbations.

SCALLOPS improves processing of optical pooled screens by enabling efficient alignment and analysis of large-scale image data, demonstrating superior performance over existing methods.

The paper introduces PerturbPair, a platform integrating transcriptomic and optical screens to map macrophage regulatory networks, revealing cross-modal relationships and disease-relevant gene programs.

This study uses dynamic caging to link live-cell behavior with transcriptional responses across perturbations, revealing new insights into immune and inflammatory gene regulation.

This paper develops a degron-modified Cas12a system to enable accurate single-cell detection of pre-crRNAs, enhancing Perturb-seq capabilities for multiplex guide expression.

PerturbView enables highly multiplexed optical pooled screens in primary cells and tissues by improving barcode amplification, revealing regulators of NFκB signaling and enabling spatial transcriptomics integration.

This paper introduces SC-VAE, a supervised contrastive framework for analyzing cell perturbation data, showing improved sensitivity in detecting perturbation effects compared to existing methods.

This paper introduces an active learning method to efficiently design Perturb-seq experiments by leveraging multi-modal priors, improving perturbation space exploration with fewer experiments.

The paper introduces a contrastive analysis framework to disentangle perturbation effects from natural cell variation in optical pooled screens, showing improved performance in generating embeddings and reducing technical artifacts.

The paper identifies a dynamic HIF1alpha-PPARgamma circuit that both promotes and represses lipid accumulation during adipogenesis, revealing a mechanism for adipocyte dysfunction in obesity.

DeepCell Kiosk scales deep learning workflows for large imaging datasets, processing 106 images in ~5.5 hours at a low cost.