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TIMING 2.0: high-throughput single-cell profiling of dynamic cell–cell interactions by time-lapse imaging microscopy in nanowell grids
Author(s) -
Hengyang Lu,
Jiabing Li,
Melisa Martinez-Paniagua,
Irfan Bandey,
Amit Amritkar,
Harjeet Singh,
David Mayerich,
Navin Varadarajan,
Badrinath Roysam
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty676
Subject(s) - computer science , graphical user interface , python (programming language) , profiling (computer programming) , software , source code , interface (matter) , sample (material) , operating system , bubble , chromatography , maximum bubble pressure method , chemistry
Automated profiling of cell-cell interactions from high-throughput time-lapse imaging microscopy data of cells in nanowell grids (TIMING) has led to fundamental insights into cell-cell interactions in immunotherapy. This application note aims to enable widespread adoption of TIMING by (i) enabling the computations to occur on a desktop computer with a graphical processing unit instead of a server; (ii) enabling image acquisition and analysis to occur in the laboratory avoiding network data transfers to/from a server and (iii) providing a comprehensive graphical user interface.

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