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https://www.selleckchem.com/products/OSI-906.html Interpretation of gene expression uses set enrichment or overrepresentation methods that depend on sets of annotated genes, such as the popular Gene Ontology. The placenta is understudied relative to other major organs creating a deficit of molecular and functional knowledge about this organ. The lack of placental and trophoblast research significantly impacts our ability to interpret the results of high throughput experiments. Gene sets were generated by a semi-automated re-analysis of 330 microarray and 91 RNA sequencing experiments involving placental and trophoblast samples, excluding those related to pathology. Microarray data was obtained from the Gene Expression Omnibus and processed using the R package limma. RNA-sequencing data was extracted from the short read archive and processed using Kallisto and limma. The workflow consisted of quality control for experimental design and data. Sets were generated by pairwise differential expression with a maximum of 200 genes per set. We created 235 human placenta and trophoblast specific gene sets and found unique subnetworks relative to Gene Ontology. We applied these new placental gene sets to the investigation of preeclampsia and fetal growth restriction as well as invasive tumors and cell models finding matching terms related to cell types and oxygen tension (hypoxia). The human placental gene sets provide an improved context for interpretation of high throughput gene expression studies on placental pathologies beyond the Gene Ontology. Significant enrichment of placental gene sets to cancer samples and cell models indicates a utility beyond applications to placental and trophoblast cells. The human placental gene sets provide an improved context for interpretation of high throughput gene expression studies on placental pathologies beyond the Gene Ontology. Significant enrichment of placental gene sets to cancer samples and cell models indicates a utility beyond a

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