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Nat Commun ; 9(1): 226, 2018 01 15.
Article in English | MEDLINE | ID: mdl-29335532

ABSTRACT

Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of capturing individually targeted cells using widely available techniques. Using high-resolution microscopy, laser microcapture microscopy, image analysis, and machine learning, our technology enables scalable molecular genetic analysis of single cells, targetable by morphology or location within the sample.


Subject(s)
Cell Separation/methods , Image Processing, Computer-Assisted/methods , Microscopy, Confocal/methods , Single-Cell Analysis/methods , Animals , Cells, Cultured , Gene Expression Profiling , Humans , Machine Learning , Pyramidal Cells/cytology , Pyramidal Cells/metabolism , Reproducibility of Results
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