Hirofumi Kobayashi

TL;DR: Raman image-activated cell sorting is demonstrated by directly probing chemically specific intracellular molecular vibrations via ultrafast multicolor stimulated Raman scattering (SRS) microscopy for cellular phenotyping and holds promise for numerous applications that were previously difficult or undesirable with fluorescence-based technologies.

TL;DR: This protocol describes how to perform high-throughput imaging flow cytometry by optofluidic time-stretch microscopy and uses computational tools such as compressive sensing and machine learning for handling the cellular ‘big data’.

TL;DR: This work combined genome engineering, confocal live-cell imaging, mass spectrometry, and data science to systematically map the localization and interactions of human proteins, and shows that proteins that bind RNA form a separate subgroup defined by specific localization and interaction signatures.

TL;DR: A confocal fluorescence microscope that surpasses the highest possible frame rate constrained only by the fluorescence lifetime of fluorophores, and is demonstrated at a record high frame rate of 16,000 frames/s.

TL;DR: A label-free method for evaluating cellular drug responses only by high-throughput bright-field imaging with the aid of machine learning algorithms is presented and it is demonstrated that dose-dependent, drug-induced morphological change from different experiments can be inferred from the classification accuracy of a single classification model.