TIMING 2.0: high-throughput single-cell profiling of dynamic cell–cell interactions by time-lapse imaging microscopy in nanowell grids

Abstract

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Aug 01, 2018
Source ID
10.1093/bioinformatics/bty676

Entities

People

  • Amit Amritkar
  • Badrinath Roysam
  • David Mayerich
  • Harjeet Singh
  • Hengyang Lu
  • Irfan Bandey
  • Jiabing Li
  • Melisa A Martinez-paniagua
  • Navin Varadarajan

Organizations

  • Cancer Prevention and Research Institute of Texas
  • Congressionally Directed Medical Research Programs
  • Melanoma Research Alliance
  • National Institutes of Health
  • National Science Foundation
  • University of Houston
  • University of Texas at Austin

Tags

Fields of Study

  • Biology

Readers

  • Computer Vision.
  • Distributed Systems and Data Platform Development
  • Parallel and Distributed Computing.

Technology Areas

  • Biotechnology
  • Biotechnology - Cancer Biotech