Chemical Genetic Screening Approaches to Neurobiology Brent R Stockwell  Neuron  Volume 36, Issue 4, Pages 559-562 (November 2002) DOI: 10.1016/S0896-6273(02)01056-5

Figure 1 An Example of an Imaging-Based Assay that Could Be Adapted for High-Throughput Screening Survival Motor Neuron (SMN) is shown to be localized in the growth cone of retinoic acid-treated mouse P19 embryonal carcinoma cells. SMN is stained in green, GAP-43 (a growth cone marker) in red, the nucleus in blue, and colocalized SMN and GAP-43 in yellow. The arrowhead indicates a growth cone-like structure (Fan and Simard, 2002). Figure reprinted by permission of Oxford University Press (L. Fan and L.R. Simard, Human Molecular Genetics 11, 1605–1614). Neuron 2002 36, 559-562DOI: (10.1016/S0896-6273(02)01056-5)

Figure 2 Optimization of the Z Factor during Assay Development A positive control and a negative control are used to optimize assay conditions such that the separation between the mean of the positive signal (μ+) and the mean of the negative signal (μ−) is maximized. Simultaneously, the variability of the positive (σ+) and negative (σ−) signal is minimized. The Z factor, which is defined as Z = 1 − {[3 × (σ+ + σ−)]/(μ+ − μ−)}, incorporates all of these parameters and is used as a quantitative score of assay quality (Zhang et al., 1999). Neuron 2002 36, 559-562DOI: (10.1016/S0896-6273(02)01056-5)