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: Research Article Comparison of Gene Regulatory Networks via Steady-State Trajectories | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2007 Article ID 82702 11 pages doi 2007 82702 Research Article Comparison of Gene Regulatory Networks via Steady-State Trajectories Marcel Brun 1 Seungchan Kim 1 2 Woonjung Choi 3 and Edward R. Dougherty1 4 5 1 Computational Biology Division Translational Genomics Research Institute Phoenix AZ 85004 USA 2 School of Computing and Informatics Ira A. Fulton School of Engineering Arizona State University Tempe AZ 85287 USA 3 Department of Mathematics and Statistics College of Liberal Arts and Sciences Arizona State University Tempe AZ 85287 USA 4 Department of Electrical and Computer Engineering Texas A M University College Station TX 77843 USA 5 Cancer Genomics Laboratory Department of Pathology University of Texas . Anderson Cancer Center Houston TX 77030 USA Received 31 July 2006 Accepted 24 February 2007 Recommended by Ahmed H. Tewfik The modeling of genetic regulatory networks is becoming increasingly widespread in the study of biological systems. In the abstract one would prefer quantitatively comprehensive models such as a differential-equation model to coarse models however in practice detailed models require more accurate measurements for inference and more computational power to analyze than coarse-scale models. It is crucial to address the issue of model complexity in the framework of a basic scientific paradigm the model should be of minimal complexity to provide the necessary predictive power. Addressing this issue requires a metric by which to compare networks. This paper proposes the use of a classical measure of difference between amplitude distributions for periodic signals to compare two networks according to the differences of their trajectories in the steady state. The metric is applicable to networks with both continuous and discrete values for both time and state and it possesses the critical property that it allows the comparison of networks of
