Originally a medical doctor, Kauffman is an emeritus professor of biochemistry at the University of Pennsylvania, and a seminal member and an external professor of the Santa Fe Institute. Also a MacArthur Fellow and a Trotter Prize winner, Kauffman has published three major books, among them is At Home in the Universe: The Search for the Laws of Self- Organization and Complexity(1995), which the Oxford University Press says “weaves together the excitement of intellectual discovery and a fertile mix of insights to give the general reader a fascinating look at this new science − and at the forces for order that lie at the edge of chaos.” The FidiPro program brings Kauffman to Tampere University of Technology. The subject of the program is stochastic modeling of gene regulatory networks. The project will focus on modeling the gene regulatory networks using gene expression data. The expertise of the Institute for Biocomplexity and Informatics and the modeling experience of the CSB-group led by professor Olli Yli-Harja support each other very well. The results are expected to help in understanding the mechanisms of diseases so that diseases could be identified in an early phase. They are also to be used in predicting the individual effects of different medicines therefore helping to select the best possible treatment for each patient. Stuart Kauffman is also the director of the Institute for Biocomplexity and Informatics (IBI). He is the pioneer and the founding father of biocomplexity research. Kauffman was able to look at gene regulatory networks from a new and different point of view, and it was this ground-breaking perspective that has ever since attracted new researchers and scientists worldwide. Kauffman himself got interested in gene regulatory networks at San Francisco medical school in 1964 when he wanted to unravel the mysteries of cell differentiation. Quickly noticing the possibilities of his revolutionary ideas, he started working on biocomplexity and was eventually able to show that the behaviour of genetic networks depends critically on the level at which the genes are connected.
