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The new coronavirus infection (COVID-19) that appeared suddenly has permeated our daily lives and changed our way of life. In the field of education, education is being conducted in a non-face-to-face teaching method to prevent the spread of coronavirus. In the end, e-Learning, a new educational and training system that can provide a lifelong education environment in the 21st century information society, is increasing in use in the field of education. The biggest advantage of the online education system is that it provides an environment in which you can learn the necessary contents anytime, anywhere. However, there are cases in which the learning effect is reduced because various learning support is not available in the online space due to the sudden change of the educational environment due to the COVID-19. Therefore, in this thesis, a study was conducted to analyze the learning effect of online education with voice signals for college students who are receiving education through an online education environment. To this end, the learning effect was classified into a group saying that the learning effect increased and a group that decreased due to online education, and the voices of the subjects in each group were collected. As a result of the experiment, the results of the vocal cord vibration (Pitch), Degree of voice breaks, Jitter and Shimmer were consistent among the elements of voice signal analysis between two groups.

Regenerative therapeutic approaches for myocardial diseases often involve delivery of stem cells expanded ex vivo. Prior studies indicate that cell culture conditions affect functional and phenotypic characteristics, but relationship(s) of cultured cells derived from freshly isolated populations and the heterogeneity of the cultured population remain poorly defined. Functional and phenotypic characteristics of ex vivo expanded cells will determine outcomes of interventional treatment for disease, necessitating characterization of the impact that ex vivo expansion has upon isolated stem cell populations. Single-cell RNA-Seq profiling (scRNA-Seq) was performed to determine consequences of culture expansion upon adult cardiac progenitor cells (CPCs) as well as relationships with other cell populations. Bioinformatic analyses demonstrate that identity marker genes expressed in freshly isolated cells become undetectable in cultured CPCs while low level expression emerges for thousands of other genes. Transcriptional profile of CPCs exhibited greater degree of similarity throughout the cultured population relative to freshly isolated cells. Findings were validated by comparative analyses using scRNA-Seq datasets of various cell types generated by multiple scRNA-Seq technology. Increased transcriptome diversity and decreased population heterogeneity in the cultured cell population may help account for reported outcomes associated with experimental and clinical use of CPCs for treatment of myocardial injury.

To broaden our understanding of the evolution of gene regulation mechanisms, we generated occupancy profiles for 34 orthologous transcription factors (TFs) in human-mouse erythroid progenitor, lymphoblast and embryonic stem-cell lines. By combining the genome-wide transcription factor occupancy repertoires, associated epigenetic signals, and co-association patterns, here we deduce several evolutionary principles of gene regulatory features operating since the mouse and human lineages diverged. The genomic distribution profiles, primary binding motifs, chromatin states, and DNA methylation preferences are well conserved for TF-occupied sequences. However, the extent to which orthologous DNA segments are bound by orthologous TFs varies both among TFs and with genomic location: binding at promoters is more highly conserved than binding at distal elements. Notably, occupancy-conserved TF-occupied sequences tend to be pleiotropic; they function in several tissues and also co-associate with many TFs. Single nucleotide variants at sites with potential regulatory functions are enriched in occupancy-conserved TF-occupied sequences.