Synthesizing Systems Biology Knowledge from Omics Using Genome-Scale Models

Sanjeev Dahal, James T. Yurkovich, Hao Xu, Bernhard O. Palsson, Laurence Yang
2020 Proteomics  
Omic technologies have enabled the complete readout of the molecular state of a cell at different biological scales. In principle, the combination of multiple omic data types can provide an integrated view of the entire biological system. This integration requires appropriate models in a systems biology approach. Here, we focus on genome-scale models (GEMs) as one computational systems biology approach for interpreting and integrating multi-omic data. GEMs convert the reactions (related to
more » ... olism, transcription and translation) that occur in an organism to a mathematical formulation that can be modeled using optimization principles. We review a variety of genome-scale modeling methods used to interpret multiple omic data types, including genomics, transcriptomics, proteomics, metabolomics, and meta-omics. The ability to interpret omics in the context of biological systems has yielded important findings for human health, environmental biotechnology, bioenergy, and metabolic engineering. We find that concurrent with advancements in omic technologies, genome-scale modeling methods are also expanding to enable better interpretation of omic data. Therefore, we expect continued synthesis of valuable knowledge through the integration of omic data with GEMs. This article is protected by copyright. All rights reserved.
doi:10.1002/pmic.201900282 pmid:32579720 fatcat:h3euvl3j5vggjmbh5buaspz4uy