In , at the age of 32, he was named the Emil T. Hofman Professor of Physics, becoming the youngest endowed professor. In he founded the Center for Complex Network Research. In —06 he was a Visiting Professor at Harvard University. His biggest role has been the discovery of the scale-free network concept.
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Silverman Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. Network Medicine introduces this rapidly evolving field of medical research, which promises to revolutionize the diagnosis and treatment of human diseases.
With contributions from leading experts that highlight the necessity of a team-based approach in network medicine, this definitive volume provides readers with a state-of-the-art synthesis of the progress being made and the challenges that remain. Medical researchers have long sought to identify single molecular defects that cause diseases, with the goal of developing silver-bullet therapies to treat them.
But this paradigm overlooks the inherent complexity of human diseases and has often led to treatments that are inadequate or fraught with adverse side effects. Rather than trying to force disease pathogenesis into a reductionist model, network medicine embraces the complexity of multiple influences on disease and relies on many different types of networks: from the cellular-molecular level of protein-protein interactions to correlational studies of gene expression in biological samples.
By developing techniques and technologies that comprehensively assess genetic variation, cellular metabolism, and protein function, network medicine is opening up new vistas for uncovering causes and identifying cures of disease. A revolutionary new theory showing how we can predict human behavior.
Can we scientifically predict our future? Scientists and pseudo scientists have been pursuing this mystery for hundreds and perhaps thousands of years. But now, astonishing new research is revealing patterns in human behavior previously thought to be purely random. Precise, orderly, predictable patterns His approach relies on the digital reality of our world, from mobile phones to the Internet and email, because it has turned society into a huge research laboratory.
All those electronic trails of time stamped texts, voicemails, and internet searches add up to a previously unavailable massive data set of statistics that track our movements, our decisions, our lives. Analysis of these trails is offering deep insights into the rhythm of how we do everything. His finding? We work and fight and play in short flourishes of activity followed by next to nothing.
Bursts reveals what this amazing new research is showing us about where individual spontaneity ends and predictability in human behavior begins. The way you think about your own potential to do something truly extraordinary will never be the same. Find here Amazon BN. In Bursts, he shows us how they unfold in time. Your life may look random to you, but everything from your visits to a web page to your visits to the doctor are predictable, and happen in bursts.
These bursts are both mathematically predictable and beautiful. What a joy it is to read him. You feel like you have emerged to see a new vista that, while it had always been there, you had just never seen.
Christakis, M. Whether or not the concept of "burstiness" is the key to unlocking human behavior, it is nonetheless a fascinating new way to think about some very old questions. Madden, Ph. Here, the physicist shows how to use that knowledge to predict seemingly random human behavior. Or the spread of a viral epidemic through populations. Or the convoluted trails that money follows. The effect is enthralling: less like listening to a lecture at a research conference, and more like sitting at a bar with a clever friend who charms you with his semi-implausible anecdotes.
Barabási Albert László