PyCLM: programming-free, closed-loop microscopy for real-time measurement, segmentation, and optogenetic stimulation.

ABSTRACT: In cell biology, optical techniques are increasingly used to measure cells' internal states (biosensors) and to stimulate cellular responses (optogenetics). Yet the design of all-optical experiments is often manual: a pre-determined stimulus pattern is applied to cells, biosensors are measured over time, and the resulting data is processed off-line. With the advent of machine learning for segmentation and tracking, it becomes possible to envision closed-loop experiments where real-time information about cells' positions and states are used to dynamically determine optogenetic stimuli to alter or control their behavior. Here, we develop PyCLM, a Python-based suite of tools to enable real-time measurement, image segmentation, and optogenetic control of thousands of cells per experiment. PyCL

SUBMITTER: Oatman HR 

PROVIDER: S-EPMC12424725 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature