The ability to assign expression patterns to the individual cell types that constitute a tissue is a major challenge. This especially applies to brain, given its plethora of different, functionally interconnected cell types. Here, we derived cell type-specific transcriptome signatures from existing single cell RNA data and integrated these signatures with a newly generated dataset of expression (bulk RNA-Seq) of the postnatal developing mouse hippocampus. This integrated analysis allowed us to provide a comprehensive and unbiased prediction of the differentiation drivers for 11 different hippocampal cell types and describe how the different cell types interact to support crucial developmental stages. Our results provide a reliable resource of predicted differentiation drivers and insights into the multifaceted aspects of the cells in hippocampus during development.