The architectural extension of “omics” to a molecular level describes the comprehensive and global assessment of molecules at a systemic level. The original omics discipline was emerged from genomics, concentrated on the knowledge of complete genomes as argued to “genetics” that questioned particularly about genes. However, merely understanding genomics data does not allow to understand the physiological response of the cellular mechanism. In this context, the integration of several multi-omics data types has provided the ability to survey the global molecular expression pattern of an organism. In the early 2000s, the swift technological advancement in the field has made cost-efficient, high-throughput generation and analysis of integrated data types and are highly capable of interrogation of entire pools of transcripts, proteins, and metabolites, in the background of genome information for modeling the biologic networks. Taken together, these realizations provided a rationale for the development of systems biology technologies that involve the integration of different omics data types to identify molecular patterns associated with the specific physiological milieu and creates the concept of omics technologies for one health.
Each type of omics data, on its own, typically provides a list of different knowledge associated with its biomolecule. These data can be useful for both the identification of the markers linked to a specific process(s), to give insight as to which biological pathways or processes are different between the disease as well as control groups to improve the productivity. However, analysis of only one data type is limited to correlations, mostly reflecting reactive processes rather than causative ones. Integration of different omics data types is often used to elucidate potential causative changes that lead to disease, or the treatment targets, that can be then tested in further molecular studies.
The ICPBHF-2019 will consist of a variety of plenary and parallel sessions, aimed to discuss the recent highlights, implementation of methodologies in statistics, missing data, study design role play, of important knowledge achieved through the application of omics technologies and proteo-genomics data in the field. Finally, speculate about the future directions of multi-omics approaches.