Thumbnail image of

During the past decades, we have witnessed extraordinary advances in experimental and computational technologies to tackle the complexity of living organisms and understand their physiology and pathologies. We know that there are two fundamental types of biological information: the digital genome and environmental signals that operate through the context of living organisms to generate both normal and diseased phenotypes. Dynamic biological networks and molecular machines connect these two types of information with the resulting phenotypes. The essence of understanding disease is thus to follow the dynamics of disease-perturbed biological networks in each individual. This dynamics of life is revealed by functional genomic analyses. Indeed, the Human Genome Project has triggered the development of a wide array of tools for high-dimensional and high-throughput comprehensive measurements of DNA, RNA, protein and metabolites to comprehensively delineate individual components of the genome, transcriptome, proteome and metabolome. The Human Physiome Project has initiated a renewal of physiology through computational integration and modeling of processes occuring across multiple scales of biological organization, from molecules and cells to tissues and organs, with the ultimate goal of obtaining computable predictive models of physiology and disease of individuals taking into account their changing environment. These two complementary research strategies now converge through implementation of systems biology approaches combining advanced molecular and imaging data to bring the concept of systems or personalized medicine one step closer to reality.

... functional genomic analysis and physiology converge through implementation of systems biology to bring personalized medicine closer to reality.

In this Special Issue of Biotechnology Journal dedicated to systems approaches to personalized medicine, Jaeyun Sung et al. [1]review the potential of molecular signatures derived from the analysis of functional genomics data to help diagnose disease and guide therapy. They discuss the hurdles that still need to be overcome to obtain robust, reproducible, sensitive and specific molecular signatures of demonstrated clinical utility in groups of patients that can then be fine-tuned to individual characteristics and medical needs. Peter Hunter and Bernard de Bono [2] highlight the role of biomedical modeling scenarios in the development and exploitation of computational models of physiology and pathology. The authors indicate the key role of data and knowledge representation standards in both approaches to enable identification of relevant functional networks perturbed in disease and targeted reversal of pathological processes on an individual basis. Placing these developments in the context of an healthcare system evolving from a focus on the detection and treatment of disease to the prevention of disease occurrence based on the analysis of individual characteristics, Ralph Snyderman [3] discusses how this can help reduce the high burden of chronic diseases. Larry Smarr [4] then shares his decade-long personal experience in quantifying his personal health state through regular quantitative monitoring of his own body, illustrating both the usefulness of integrating blood and stool biomarkers in the context of personal and gut microbiome genomes, and a very concrete meaning of participatory medicine.

These four complementary articles thus highlight how functional genomics and computational physiology can contribute to the development of predictive, preventive, personalized and participatory (P4) medicine and support a transition from the current reactive practice of medicine to a proactive empowerment of individuals to manage their health with their physicians as we discuss in our Perspective article [5]. We predict that this transition will occur through seamless exploitation, integration and modeling of a wealth of data collected regularly on each individual across all levels of biological organization in relation to environmental changes, using non-invasive measurements and advanced information and communication technologies. We expect that this will reverse the non-sustainable trend in escalating costs in diagnostics, drug development and healthcare. We are thus in the middle of a revolution (not simply an incremental evolution) in medical practice, acting as a community to catalyze a profound change with systems biology approaches.

Thumbnail image of

Prof. Charles Auffray, European Institute for Systems Biology & Medicine, Lyon, France

Thumbnail image of

Prof. Leroy Hood, Institute for Systems Biology, Seattle, WA, USA


  1. Top of page