Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Editorial Network Structure and Biological Function: Reconstruction, Modeling, and Statistical Approaches | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2009 Article ID 714985 2 pages doi 2009 714985 Editorial Network Structure and Biological Function Reconstruction Modeling and Statistical Approaches Joachim Selbig 1 Matthias Steinfath 1 and Dirk Repsilber2 1 University of Potsdam Department of Biochemistry and Biology Bioinformatics Chair 14469 Potsdam Germany 2 Genetics and Biometry unit Research Institute for the Biology of Farm Animals FBN 18196 Dummerstorf Germany Correspondence should be addressed to Dirk Repsilber repsilber@ Received 23 March 2009 Accepted 23 March 2009 Copyright 2009 Joachim Selbig et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. The question of how biological function is related to the structure and dynamics of biological regulatory networks is central to systems biological research. This relationship may be observed on different scales for example on a global scale or on the level of subnetworks or motifs. Several levels exist on which to relate biological function to network structure. Given molecular biological interactions networks may be analysed with respect to their structural and dynamical patterns which are associated with phenotypes of interest. On the other hand experimental profiles . time series and disturbances can be used to reverse engineer network structures based on a model of the underlying functional network. Is it possible to detect the decisive network structural features with the current methods How is our picture of the relationship between network structure and biological function affected by the choice of methods These questions constitute the subject of the present special issue. The authors have approached the subject from different perspectives. Experimental data analysis .
