Data Analysis Pipeline for High Content Screening in Drug Discovery - High-Throughput Image Reconstruction and Analysis - page 226

9.9 Conclusion and Future Perspectives
HCS has increasingly been adopted in many aspects of drug discovery as well
as system cell biology research. It has the potential to make major impacts on
compound mechanistic and toxicology studies. During the past 10 years of devel-
opment, many technical hurdles have been surpassed, including automated image
acquisition, basic forms of image analysis, and data storage and archiving. Here we
provide a practical basic framework on large scale HCS data analysis. We envision
that more advanced statistical methods will be adopted in the near future to better
mine the rich information contained in the HCS dataset. There are also significant
efforts spent on improving image analysis, especially for morphology based HCS,
and analysis of time lapsed datasets, as well as making basic image analysis tools
more accessible for academic research. Statistical methods to mine and compare
these rich datasets will become increasingly necessary.
Acknowledgments
We thank Jonathan Hoyt and Elizabeth McWhinnie for providing technical
support.
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