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Explore the organization of biological information in small-world and scale-free networks, and how this knowledge can be used to predict and prevent major causes of morbidity worldwide. Discover how self-organizing networks can improve healthcare in less developed countries.
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The Power of Networks for Innovation • Biological information is organized in small -world and scale-free networks where few nodes become hubs dominating the entire network. • The topology or architecture of such biological networks could be useful to predict and prevent major causes of morbidity worldwide. • This knowledge from systems biology could also be transferred and translated to better health care of less developed countries, by self-organizing networks
Information is organized into Networks • Small-world: • Highly packed • Short paths • Lethality • Centrality Scale-free: • Hubs • Rich gets richer • Hierarchical • Modular • Low error • Vulnerability Internet (global scale) Subcellular (nano scale)
Power Law(The rich gets richer) Scale-free networks: Barabási, A.L. (2002) Linked, The New Science of Networks. Perseus. Protein evolution Team assembly networks
Genome-wide association studies of common diseases Prediction of morbidity
Biological information pathways to major causes of morbidity worldwide 0 2….. 4h …..6h….// 24h // Years Time ER stress Systemic inflammatory response Network of 1,556 genes (Nature,447, 1032, 2005)
Risk Vectors Risk Estados final B Clinical Genomic Metabolic Estados Inicial A Clinical Genomic Metabolic
Key References • Rangel-Aldao R (2003) Developing countries and systems biology. Nature Biotechnology, 21, 3-4 • Rangel-Aldao R (2004) Realities for Latin American and Caribbean Biotech. Nature Biotechnology, 22, 20 • Rangel-Aldao R (2005) Innovation, Complexity, Networks and Health. Innovation Strategy Today, 1, No. 2, 46-67 • Rangel-Aldao(2007)Patenting the gene-hubs of Endoplasmic Reticulum Stress: the Systems Biology Approach. Recent Patents on Biotechnology, Vol. 1, No. 3, In the press
Summary Slide • Translational research for capacity building: from systems biology to preventative and networked health systems • Self-organizing technology transfer: integrating clinicians and scientists by autonomous and synchronized local networks • Small-world networks as a mean to bridge effective international technology transfer to less advanced countries