Models and Tools

The omics research began with genomics, which aids in the investigation of genetic variants associated with a complicated and mendelian disease. Genomic research focuses on the entire genome, as opposed to genetic research, which focuses on single genes or particular variations. The omics discipline is gaining a lot of traction as technology advances allow for more efficient study of biological molecules. Genome, proteome, transcriptome, and metabolome data are the four major forms of Omics data. Rapid improvements in high-throughput omics (genomic, transcriptomic, proteomic, and metabolomic) technology have resulted in the rapid accumulation of patient data. Biomedical research currently has a surplus of data but a scarcity of knowledge. By dealing with the storage, retrieval, and efficient use of omics data, computational bioinformatics plays a critical role in knowledge discovery. Despite significant advances in the state of knowledge and significant computational and statistical efforts in this field over the past decades, a critical issue of methodology or computational challenges in the post-genomic era of system medicine persists: how to make efficient and maximal use of the ongoing arrival of big omics data.

• Machine Learning
• Artificial Intelligence
• Systems Biology