Human pluripotent stem cells (hPSCs) are cells capable of self-renewal while differentiating into any cell type in the body. The differentiation into skeletal muscle progenitor cells (SMPCs), results in mature skeletal muscle cells. As the potential of deriving SMPCs from hPSCs has been further researched for medical application, the problem encountered is how to generate fully functional skeletal muscle cells from hPSCs experimentally. Currently, there are many existing protocols (e.g., HX, JC, MS Protocols) for such differentiation, known as myogenesis, but each has problems that need to overcome (e.g., time-consuming, not fully functional cells, resulted in other cell types). Our goal is to figure out what genes and metabolites are involved in the natural process of differentiation (from prenatal skeletal muscle progenitors to satellite cells) and apply the knowledge experimentally. To address this, we present the use of computational methods for the biological network-based integration of transcriptomic and metabolomic data. By analyzing data for both in vivo process and in vitro protocol results, we can find potential genes and metabolites differences, relating from the transcriptomic level to metabolomic level, revealing the inadequacy in the experimental protocols, presenting probable genes to improve the results. This involves RNA sequencing data analysis (e.g., single-cell, microarray) of human and mouse cells from embryonic to postnatal stages, with Seurat (pseudo-time analysis), Monocle, and AFFY, which processes/analyzes the data revealing potential genes. Then further analysis with UKIN, guided network propagation, to rank and identify the most probable genes, and perturb-Met to analyze metabolites involved. This is a time and cost-efficient way to find most probable genes directing the differentiation, which can then be tested and verified experimentally. If successful, it can be further developed into potential treatments much more effective and efficient than available medications and technologies for presently incurable musculoskeletal diseases.