Hiroshi Ochiai

This study shows cohesin maintains condensed euchromatic domains in human cells by preventing local mixing, which is crucial for transcriptional insulation.

The paper shows that chromatin modifications around genes fluctuate with transcriptional activity in mouse embryonic stem cells, revealing minute-scale coupling between histone marks and transcriptional bursts.

The paper develops a multiscale modeling pipeline to simulate chromatin organization and transcription regulation in mouse embryonic stem cells, revealing how sequence-regulated accessibility facilitates enhancer-promoter communication.

The paper shows that inter-species mRNA transfer from mouse embryonic stem cells to human pluripotent stem cells reprograms them to a naive-like state through specific transcription factors.

MEGA-FISH is a GPU-accelerated framework for spatial omics image analysis that improves processing speed and accuracy for large-scale tissue data.

This paper introduces label-free ghost cytometry (LF-GC) for cell therapy manufacturing, showing it can quantify cell count, viability, and identify cell subsets and impurities without staining.

The paper uses single-molecule imaging to show RNA fluctuations modulate SOX2 dynamics at the Nanog locus, revealing RNA-dependent feedback in transcriptional regulation.

The paper introduces PECAbs for high-specificity multiplexed imaging of cell states and combines them with seq-smFISH to classify cells and identify signal activation states in human tissue.

The paper examines enhancer-promoter interactions in mouse embryonic stem cells, finding that transcriptional activity increases genomic viscosity, stabilizing these interactions.

The paper develops a STREAMING-tag system to study spatiotemporal relationships between transcriptional factors and activity in living cells.

PHi-C simulates dynamic 3D genome features from Hi-C data, aligning with live-cell imaging observations and providing physical insights.

This study investigates transcriptional bursting kinetics in mESCs using scRNA-seq and identifies regulatory factors and pathways influencing gene expression noise.