Network medicine represents a paradigm shift in our understanding of diseases by unveiling the intricate connections among biological components, thus enabling a more holistic and precise approach to patient care. The LBI-NetMed aims to catalyze this paradigm shift by deciphering the fundamental architecture of cross-scale networks from the molecular to the whole-body level, and applying the insights to improve how diseases are diagnosed, treated, and managed.
The human body contains myriads of components that range from biomolecules to cells, tissues and organs. Modern technologies allow us to profile these components at molecular resolution, generating massive amounts of data in biological and medical research. Interpreting this data, however, poses a critical challenge in both research and clinical practice. Our limitations in interpreting these massive data, in turn, limits our ability to exploit them for practical medical applications. These limitations are not only technical, but rather conceptual, as we lack understanding of the fundamental principles governing human biology across molecular, cellular, organ, and whole-body levels.
The overarching ambition of the LBI-NetMed is to leverage network theory, machine learning and artificial intelligence to formulate a holistic view of the intricate cross-scale nature of human biology and to translate the gained insights to concrete medical impact ranging from diagnosis to treatment.
