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The objective of this study was to develop and investigate an approach to optimally detect, rank, display, and analyze patterns of differential growth inhibition among cultured cell lines. Such patterns of cellular responsiveness are produced by substances tested in vitro against disease-oriented panels of human tumor cell lines in a new anticancer screening model under development by the National Cancer Institute. In the first phase of the study, we developed a key methodological tool, the mean graph, which allowed the transformation of the numerical cell line response data into graphic patterns. These patterns were particularly expressive of differential cell growth inhibition and were conveniently amenable to further analyses by an algorithm we devised and implemented in the COMPARE computer program.
Paull et al. (Wed,) studied this question.