During very early stages of microbial infections, a series of physiological and molecular changes including differential gene expression, proteome and metabolomic interactions occur in the host. Measuring and correlating this information can allow a better understanding of the complex molecular interactions that take place in pathogenesis and disease. More importantly, the development of appropriate systems biology applications can uncover early infection biomarkers capable of discriminating healthy from disease states and help predict drug response and disease prognosis or monitor treatment with a given drug. To capture these complex host-pathogen interactions and recognize the topological differences between transcriptional networks, Orion Integrated Biosciences Inc. is developing a new generation of machine learning and artificial intelligence algorithms. This system biology approach takes advantage of all features known about the host genome and stored in our databases (e.g. molecular function, cellular localization of the genes, enzyme class, alternative splice variants, etc.). With this information, we identify molecular pathways and tempo-spatial biomarkers resulting from vaccination, drug treatment, infection specific pathogens or toxin exposures.
