Bioinformatics

This course offers an introduction to network medicine, a rapidly emerging field that integrates systems biology and network science. It runs counter to the prevailing scientific reductionist trend that dominates current medical research on disease etiology and treatment. Reductionism relies on single molecules or single genes to provide comprehensive and robust insights into the pathophysiology of complex diseases. Similarly, current drug development methodologies target single molecules that very frequently fail because of the unforeseen and unintended effects that result from the application of this piecemeal approach to pharmacology. In contrast, network medicine emphasizes a more holistic approach through the identification and investigation of networks of interacting molecular and cellular components. When network medicine is integrated into biomedical research, it has the potential to transform investigations of disease etiology, diagnosis, and treatment. The course will explore the concept of network medicine through: (1) a review of the role, identification, and behavior of networks in biology and disease, (2) the integration of multiple types of -omics data into networks as a paradigm for understanding disease expression and course, and (3) systems pharmacology approaches for the development and evaluation of effective therapies of complex disease. Moreover, this course will provide hands-on experience in the analysis of two specific types of biological networks—gene co-expression networks and drug-disease networks. During the course, attendees will apply the theory to real data sets. After completing the course, attendees should to be able to apply these methods in their own research. The course goals are: Understand the role of networks in biology and disease. Understand networks as a paradigm for disease expression and course. Understand the challenges of developing effective therapies for complex diseases. Understand the role of omics data in networks. Understand network medicine in terms of investigation for disease etiology, diagnosis, and treatment.