In this post-genomic era it is clear that the sum of the cellular gene expression state determines the cellular phenotypes. The advance in genomics technology permits the recognition of disease-associated proteins or genomic traits that may serve as clinical markers or survival indexes. The challenge we now face is to keep up the bioinformatics analysis, to understand the genome blueprint, and to determine how errors lead to disease. Bearing these in mind, we developed bioinformatics pipelines and applied systems biology tools for deciphering transcriptome data generated by gene expression microarray and RNA-Seq technologies, as well as setup wetlab functional validation platforms. Novel miRNAs were found, and their very existence could be confirmed by wetlab validation such as RNA-immunoprecipitation (RNA-IP). Our current effort is to deduce the relationships between filtrated genes and stem cell features. Further challenge will be to apply cloud computing technologies to facilitate next-generation sequencing (NGS) data, as well as to further integrate NGS information with systems biology algorithms.