• The "ome" era: What else?
Prof. Dr. Mohamed Atia Omar, Associate Professor, Genome Mapping, Genomics and Bioinformatics. AGERI, ARC.
Omics refers to the collective science-domains or technologies used to characterize and quantify pools of biological molecules and to explore their roles, relationships, and actions in the cells of a living creature. The origin of this “Omics” evolution was started with the ‘Genomics’ in the 1990s, initially after the efforts to sequence the whole human genome (and those of other organisms), and as the technology progressed rapidly, it became feasible to do this increasingly efficiently and with increasing precision. Genomics was followed by transcriptomics, proteomics, lipidomics, glycomics, metabolomics, epigenomics, metagenomics, SSRomics, etc. The volumes of big-data generated by these approaches increased rapidly across the whole of biology. Alongside, improvements in bioinformatics tools including big-data storage, high-performance computing power, and many software resources have facilitated the analysis of these massive datasets.
This lecture highlighting on how the integration of increasingly available Omics data increases our ability to segment patients/organisms into smaller and smaller cohorts, thereby prompting a shift in our thinking about how to use these Omics data. Also, lecture touching the paradigm shift from singular Omics signatures to patient cohort matching – a shift that may potentially more readily take advantage of the large repositories of Omics data that are being created. These revolutions in the ‘Omics’ eventually lead to strategic priority to focus on such “data-driven science”: approaching the mass of data with computational approaches to find commonalities, and even to identify the questions as well as the answers.
