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Data Quality for High Content Screening

Published

Author(s)

YaShian Li-Baboud, Oleg Aulov, Peter Bajcsy

Abstract

TO HAVE CONFIDENCE IN THE KNOWLEDGE GLEANED FROM DATA, IT IS ESSENTIAL TO VERIFY THE QUALITY OF THE DATA SOURCES AND TO HAVE A MEANS OF QUANTIFYING THE POTENTIAL UNCERTAINTIES DUE TO THE QUALITY OF DATA FOR MAKING CRITICAL, INTELLIGENT DECISIONS. HIGH CONTENT SCREENING (HCS) IS AN AUTOMATED MICROSCOPY TECHNIQUE ENABLING THE EVALUATION OF SPATIAL AND TEMPORAL EFFECTS ON CELLS FOR DRUG DISCOVERY AND OTHER APPLICATIONS. HIGHER THROUGHPUT OFTEN MEANS COMPROMISING THE IMAGE QUALITY. HOWEVER, SOMETIMES HIGH THROUGHPUT IS REQUIRED TO CAPTURE TRANSIENT MORPHOLOGICAL EFFECTS. UNDERSTANDING HOW TO QUANTIFY AND IMPROVE DATA QUALITY WOULD LEAD TO HIGHER CONFIDENCE IN HCS FINDINGS.
Proceedings Title
Big Data Workshop
Conference Dates
June 13-14, 2012
Conference Location
Gaithersburg, MD

Keywords

Data Quality, High Content Screening

Citation

Li-Baboud, Y. , Aulov, O. and Bajcsy, P. (2012), Data Quality for High Content Screening, Big Data Workshop, Gaithersburg, MD (Accessed March 4, 2024)
Created September 3, 2012, Updated February 19, 2017