RedHUMAN: Deciphering links between genes and metabolism

Credit: Maria Masid (EPFL) - Scientists at EPFL have developed a new method that simplifies the processing of genetic-metabolic data by picking up changes in metabolism, a hallmark of numerous diseases like cancer and Alzheimer's. The new method, named redHUMAN, is robust and features guaranteed predictability. In the last two decades, the life sciences have seen a growing partnership with information technology. The main drive behind this is the need to process and integrate enormous volumes of data from different fields including genetics, biochemistry, cell and molecular biology, and physiology in order to gain a deeper understanding of biological systems, processes, and even entire organisms. The problem is that putting together data from numerous interconnected biological networks across different strata of biological analysis (e.g. genetic vs biochemical) has proven too complicated. The sheer volume and complexity of data across multiple fields is difficult to standardize and process, and has partly caused the proliferation of different "omics" fields (e.g.