The past half century has seen a tremendous progress in technology. The first hand held mobile phones began production in 1973[1] and today about 45% of the world's population owns a smart phone.[2] In 1983, the publicly available and practical version of the internet was invented allowing standard computer networks to communicate with one another.[3] Today, it is rare to find a stand-alone computer not connected to the world wide web. Science took a historical leap forward approximately a quarter of a century ago with the development of the human genome project (HGP).[4] While the HGP was the complete mapping of all the genes in the human genome, ultimately it changed how science was approached. The ushering in of genomics via the HGP quickly led to en masse measurement of gene transcripts (transcriptomics), proteins (proteomics), and finally metabolites (metabolomics). While the knowledge gained from these branches of omics will continue to increase as time passes, one thing we have learned for certain is that the human cell is an amazing feat of engineering. Its genome is made up of approximately 20 000 protein coding genes and produces an estimated 200 000 transcripts. Within the genomic code are blueprints for potentially producing upwards of a billion protein species when various splice variants and post-translational modifications are considered. The human metabolite database currently lists over 114 000 metabolites that have either been detected or are predicted to be present within human cells.[5] Compare these numbers to an automobile, which contains on the order of tens of thousands of moving parts. Just like an automobile engine, the components of the cell work together to create a functional entity. Also like an engine, the source of a dysfunctional component within a cell may not be directly connected to the component itself. For example, rapid cell proliferation in human epidermal growth factor receptor 2 (HER-2) breast cancer is caused by an excess of HER-2 receptors on the surface of the cells.[6] The source of this receptor expansion, however, can be traced to gene duplication events. Historically, studies would be designed to identify this connection molecule by molecule, specifically targeting the protein receptor and HER-2 gene. In today's omics-era it is possible to collect data on thousands of genes, transcripts, and proteins so that not only the source of the biological problem can be detected but also the peripheral damage it creates. The systems biology era has given rise to a plethora of different omics fields that aim to characterize various aspects of cells and organisms. The foundation of systems biology, however, remains the “big-four” omics: genomics, transcriptomics, proteomics, and metabolomics. The initial article in this edition provides a reflection on the progress that has been made in omics research beginning with the HGP, which arguably changed the strategy in how scientists design biological studies.[7] The article highlights the incredible progress that has been made in the big-four omic fields. Description of an article detailing a multi-omics study of plasma samples obtained from individuals infected with COVID-19 demonstrates how mainstream systems biology studies have become in just the past few years. While the article also highlights challenges in systems biology, it provides a glimpse into the many different databases and consortiums that have arisen to address the ambitious nature of attempting to characterize all the components within cells and organisms. While much effort has been spent in the past couple of decades identifying the entire complement of cellular biomolecules, the need to identify how these biomolecules interact to carry out the many functions that occur within these cells has become paramount. In their article, Basu et al., describe the use of functional proteomics and systems biology to generate protein-protein interaction networks in neurons, glia, and other cell types.[8] They summarize findings from recent studies that compare these interaction networks in normally functioning neurons, in developing neurons, and neurodegenerative diseases. The article goes on to demonstrate how these interaction networks can be used to decipher cellular functions that regulate neuronal activity and brain function. While the era of systems biology has increased the amount of data per study, most laboratories are not historically designed to accommodate this requirement. A complete systems biology view of a cell requires data from a variety of classes of biomolecules (e.g., DNA, RNA, proteins, etc.), however, most labs are designed to analyze only one (or possibly two) of these classes. Another barrier to limited lab resources is the ability to integrate data from multiple similar investigations to test the veracity of hypotheses that may be generated from omic studies. In their review, Mantini et al. describe various methods for integrating phosphoproteomic data particularly in the context of cancer research.[9] They proceed to present various methods that enable phosphoproteomic data to be integrated with data from other omic fields to provide a broader systems biology perspective. As briefly mentioned in the initial article of this special edition, a number of researchers are working towards generating omics data on single cell as a means of avoiding the inherent heterogeneity of cell populations. In an application of this area, Zhiyuan et al. developed a novel integrated microfluidic chip capable of isolating and characterizing the RNA expression profile of a single circulating cancer cells (CTCs).[10] While CTCs are effective for monitoring tumor metastasis, they are also heterogeneous. To validate their device, Zhiyuan et al. performed transcriptome profiling of single MCF-7 and white blood cells. When the transcriptomic profiles of the two cell types were compared significant genetic differences were observed based on three different measures. While proteomic diversity is mostly a result of cell-mediated post-translational modifications and the post-transcriptional occurrence of splice variants, there are many exogenous compounds that can modify proteins within the proteome.[11] In an article illustrating how dynamic the proteome can be, Tocmo et al. review how plant-derived natural products can covalently modify proteins.[13] In their article they describe how various proteomic techniques are used to identify various modifications derived from plant-based natural products can alter protein conformation, resulting in an alteration of their function and the biological activity that they modulate. One of the major benefits of the omics-era has been the discovery of the vast diversity of the biomolecules that make up cells. As scientists develop more creative uses of technologies, the number of known variations of biomolecules continues to increase. In their article, Muroski et al. build upon the observation that cyclized immonium ions that are observed in the tandem mass spectrometry (MS) spectra of acylated lysine residues could be used to identify acyl-lysine modifications.[14] They developed a stepped collision energy method that provides unique features in the tandem MS spectra of acyl-lysine containing peptides by optimizing the abundance of the immonium ion without sacrificing the information available to identify the modified peptide's sequence. Testing this novel MS method on a proteome extracted from Synotrophus aciditrophicus that had been spiked with three peptides that differed in their type and location of acetylation. This novel stepped collision energy method was able to successfully identify each of the three peptides within a complex background of peptides. In a further application, the researchers were able to identify, for the first time, a hydroxypimelyl-lysine residues within the Synotrophus aciditrophicus proteome. There is a basic paradigm in protein science that structure dictates function. But what about proteins that do not have a unique stable structure? So-called intrinsically disordered proteins (IDPs) are known to affect many cellular processes and have even been associated with diseases. The challenge, however, has been identifying and deciphering the mechanisms of this atypical class of proteins. Conventional techniques such as X-ray crystallography and nuclear magnetic resonance spectroscopy are designed to characterize stable structures within proteins but generally fail when dealing with unstructured domains. The article not only highlights the impact that MS has had on characterizing IDPs but discusses the future potential of this technique in uncovering further facets of this underexplored group of proteins.[15] Oxylipins are a family of oxygenated natural products derived from polyunsaturated fatty acids by the action of cyclooxygenase (COX) and lipoxygenase enzymes.[15] These highly potent molecules stimulate a variety of biological responses including inflammation, vasoconstriction, vasodilation, blood-clotting, etc. in response to tissue injury. In a combined targeted proteomics/metabolomics approach Scheb et al. developed a selected reaction monitoring-MS assay to measure the absolute abundance of the COX-2 enzyme and compared changes in its level to changes in the abundance of a panel of oxylipins.[16] They applied this method to study the association between COX-2 and oxylipin levels in the human colon carcinoma cell lines and lipopolysaccharide-stimulated macrophages. This combined, targeted omics approach has the potential to be expanded to include additional enzymes involved in oxylipin synthesis and can be used to further elucidate the biological mechanisms that modulate the response to tissue injury from exogenous and endogenous sources. I would like to express my deepest gratitude to all of the contributors who made this special issue possible. This past year is unlike any other that we have lived through. Even with all of the changes each of the contributors had to make to their labs and day-to-day duties because of the COVID-19 pandemic, they were generous enough to share their time to prepare an article for this issue. My hope as editor is that the reader will be impressed by the progress made in omics research in the recent past and be excited about what the next few years of continuing developments will reveal about the human organism. The author declares no conflict of interest.