Stem cell (SC) differentiation towards somatic cells has proven to be an effective technique in the understanding and progression of regenerative medicine. Despite improvements, concerns regarding the efficiency of differentiation and the differences between SC products and their in vivo counterparts must be addressed. Biomaterials that mimic endogenous growth conditions represent one recent method used to improve the quality and efficiency of SC differentiation. Here, we aim to use bioinformatics approaches to accomplish two aims: 1) determine the effect of different biomaterials on SC growth and differentiation, and 2) understand the effect of cell of origin on the differentiation potential of multipotent SCs. First, we demonstrate that the dimensionality (2D versus 3D) and the degradability of biomaterials affects the way that the cells are able to grow and differentiate at the transcriptional level. Additionally, the particular cell of origin is an important factor in determining the response of SCs to same biomaterial transcriptionally. Our data demonstrates the ability of bioinformatics to understand novel molecular mechanisms and context by which SCs are most efficiently able to differentiate. These results and strategies may suggest proper combinations of biomaterials and SCs to achieve high differentiation efficiency and functionality of desired cell types.