Allows calculation of a specific regulatory signal in a complex system without treating each transcription factor (TF) and cofactor in isolation. APG model permits inferring TF activities and network structures in an accurate manner from high throughput biological data. This tool takes in consideration combinatorial interactions among TFs and cofactors, thereby enabling users to apply it to: a wide class of biological data; or solve real biological problems without treating each TF and cofactor in isolation.
Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, CAS, Shanghai, China; Beijing Institute of Genomics, CAS, Beijing, China; Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, China; National Center for Mathematics and Interdisciplinary Sciences, CAS, Beijing, China; Institute of Industrial Science, University of Tokyo, Tokyo, Japan; Department of Biomedical Informatics and Center for Computational Biology and Bioinformatics, Columbia University, New York, NY, USA
APG model funding source(s)
Supported by grants from Major State Basic Research Development Program of China (973 Program) under No.2011CB504003; National Natural Science Foundation of China under No. 61134013, No. 81070657, Nos.61072149, 91029301, and No.11131009; NN-CAS Research Foundation under No. NNCAS-2009-1; Shanghai Pujiang Program; Chief Scientist Program of Shanghai Institutes for Biological Sciences, CAS under No. 2009CSP002; the FIRST program from JSPS initiated by CSTP.