Introduction to Omics
Omics technologies also referred as high-dimensional biology encompasses the cells, tissues, and organisms in a manner that integrates the data from various platforms and helps in its interpretation. It primarily detects the genes (genomics), mRNAs (transcriptomics), proteins (proteomics), and metabolites (metabolomics) in a nontargeted and non-biased manner. The integration and interrelationships between networks of biological processes is termed as systems biology. The approach provides hope for unravelling the intricate details in various aspects of biology and accelerates innovation in healthcare. Understanding the various dimensions encompassing not only the three levels constituting the central dogma of life but also the intermediate metabolites is significant for the scientists to cover new horizons in drug discovery and disease regulation. This chapter outlines the scope of omics, experimental design in omics research, and its applications. It will also provide an overview to the usage of languages like R for analyzing high-throughput data from all branches of “omics” technologies.
The primary focus is to understand omics approaches that enable the validation of large-scale data that is generated from various experimental platforms. Systems biology and omics data are way apart from hypothesis-driven traditional studies. The systems biology experiments generate hypothesis by employing all data that needs to be further analyzed.
Omics technology applied majorly for accurate understanding of normal physiological processes and gaining knowledge related to disease processes which involves screening, diagnosis, and prognosis that provides an understanding of the etiology of diseases.
KeywordsOmics Systems biology R language
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