Bioinformatics Approaches to Stem Cell Research

Purpose of Review This review article provides an overview of the bioinformatics frameworks developed in recent years that will facilitate analysis and promote the application of stem cells to medical research. Recent Findings High-throughput profiling techniques at the transcript, epigenetic, and proteomic level have uncovered unique molecular signatures of stem cells that underlie their powerful capacity. A central question in stem cell research has been: “to what extent do ‘induced’ cells resemble their in vivo counterparts?” Although studies have shown overall similarity between in vitro engineered cells and their in vivo counterparts, significant deviations that lead to functional aberrations have been identified, both between pluripotent stem cell types (e.g., ESCs vs. iPSCs) and between in vitro differentiated specialized cells and their in vivo counterparts (e.g., induced pancreatic cells vs. in vivo pancreatic cells). A number of bioinformatics approaches have emerged during the past several decades, either for classification of multiple stem cell lines based on their overall molecular patterns, or for further in-depth exploration and identification of regulatory markers that can be used for differentiating cell lines or for lineage conversions. Summary Advancements in bioinformatics approaches in stem cell research will enhance our ability to define molecular signatures of stem cells and will accelerate the application of these stem cells to regenerative medicine.