Functional profiling technologies using arrayed collections of genome-scale siRNA and cDNA arrayed libraries enable the comprehensive global analysis of gene function. However, the current repertoire of high-throughput detection methodologies has limited the scope of cellular phenotypes that can be studied. In this report, we describe the systematic identification of mammalian growth-regulatory factors achieved through the integration of automated microscopy, pattern recognition analysis, and cell-based functional genomics. The effects of 7364 human and mouse proteins, encoded by individually arrayed cDNAs, upon proliferation and viability in U2OS osteosarcoma cells were evaluated in a live-cell, kinetic assay using quantitative image analysis. Overexpression of more than 86 cDNAs (1.15%) conferred dramatic increases in the proliferation, as determined cell enumeration. These included several known growth regulators, as well as previously uncharacterized ones (LRRK1, Ankrd25). In addition, novel functional roles for two genes (5033414D02Rik, 2810429O05Rik), now termed Gatp1 and Gatp2, respectively, were identified. Further analysis demonstrated that these encoded proteins promoted cellular proliferation and transformation in primary cells. Conversely, cells depleted for Gatp1 underwent apoptosis upon serum reduction, suggesting that Gatp1 is essential for cell survival under growth-factor-restricted conditions. Taken together, our findings offer new insight into the regulation of cellular growth and proliferation, and demonstrate the value and feasibility of assessing cellular phenotypes through genome-level computational image analysis.