Preterm birth affects 1 out of every 10 infants in the United States, resulting in substantial neonatal morbidity and mortality. Currently, there are few predictive markers and few treatment options to prevent preterm birth. A healthy, functioning placenta is essential to positive pregnancy outcomes. Previous studies have suggested that placental pathology may play a role in preterm birth etiology. Therefore, we tested the hypothesis that preterm placentae may exhibit unique transcriptomic signatures compared to term samples reflective of their abnormal biology leading to this adverse outcome. We aggregated publicly available placental villous microarray data to generate a preterm and term sample dataset (n = 133, 55 preterm placentae and 78 normal term placentae). We identified differentially expressed genes using the linear regression for microarray (LIMMA) package and identified perturbations in known biological networks using Differential Rank Conservation (DIRAC). We identified 129 significantly differentially expressed genes between term and preterm placenta with 96 genes upregulated and 33 genes downregulated (P-value <0.05). Significant changes in gene expression in molecular networks related to Tumor Protein 53 and phosphatidylinositol signaling were identified using DIRAC. We have aggregated a uniformly normalized transcriptomic dataset and have identified novel and established genes and pathways associated with developmental regulation of the placenta and potential preterm birth pathology. These analyses provide a community resource to integrate with other high-dimensional datasets for additional insights in normal placental development and its disruption.