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Multicellular organisms in biology possess invaluable characteristics, which artificial systems in engineering lack, such as adaptivity and robustness. Modeling biologically inspired multicellular developmental systems in evolutionary computation have been considered for a number of years, and there exist many developmental simulations that capture multicellular characteristics of biological organisms. However, the relative importance of many mechanisms in such models is still poorly understood. This paper undertakes a detailed investigation of the importance of many mechanisms and parameters on the organizational behavior of a gene regulatory network based artificial developmental system via classical pattern matching experiments. The work leads to an improved understanding of artificial multicellular development, which will assist in its utilization in the application of evolutionary computation. It may also provide a better understanding of mechanisms of biological development.