What is Omics?
Big data often refers to large volumes of data and can be sourced from many environments. The wide variety of data types are also often generated, collected and processed quickly.
The use of the suffix Omics has increased over the past few decades because of high-throughput technologies such as mass spectrometry for proteomics and metabolomics, and massively parallel technologies such as next-generation sequencing for genomics.
Omics is shorthand for the collective, large-scale sciences that study genes (genOMICS), proteins (proteOMICS), and metabolites (metabolOMICS) to better understand the structure and function of cells or organisms.
But what is the difference between genetICS and genOMICS, for example? It’s about scale; genomics looks at the whole genome or thousands of genetic markers at a time.
Similarly, proteomics studies include thousands of proteins at once rather than a few at a time.
All OMICS technologies are underpinned and connected by the need for appropriate Bioinformatics tools and workflows that can then help visualise the data in a manner that makes it easier to pull out the underlying story from the data.