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Stem cell differentiation towards various somatic cells and body organs has proven to be an effective technique in the understanding and progression of regenerative medicine. Despite the advances made, concerns regarding the low efficiency of differentiation and the remaining differences between stem cell 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 stem cell differentiation, though the mechanisms of this improvement remain to be completely understood. The effectiveness of various biomaterials can be analyzed through a multidisciplinary approach involving bioinformatics and systems biology tools. Here, we aim to use bioinformatics to accomplish two aims: 1) determine the effect of different biomaterials on stem cell growth and differentiation, and 2) understand the effect of cell of origin on the differentiation potential of multipotent stem cells. 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, according to transcriptional state of the cells, the particular cell of origin is an important factor in determining the response of stem cells to same biomaterial. Our data demonstrates the ability of bioinformatics to understand novel molecular mechanisms and context by which stem cells are most efficiently able to differentiate. These results and strategies can be used to suggest proper combinations of biomaterials and stem cells to achieve high differentiation efficiency and functionality of desired cell types. |
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