title: TEMPI: probabilistic modeling time-evolving differential PPI networks with multiPle information.
abstract: BACKGROUND
  Time-evolving differential protein-protein interaction (PPI) networks are essential to understand serial activation of differentially regulated (up- or downregulated) cellular processes (DRPs) and their interplays over time. Despite developments in the network inference, current methods are still limited in identifying temporal transition of structures of PPI networks, DRPs associated with the structural transition and the interplays among the DRPs over time.
  
  
  RESULTS
  Here, we present a probabilistic model for estimating Time-Evolving differential PPI networks with MultiPle Information (TEMPI). This model describes probabilistic relationships among network structures, time-course gene expression data and Gene Ontology biological processes (GOBPs). By maximizing the likelihood of the probabilistic model, TEMPI estimates jointly the time-evolving differential PPI networks (TDNs) describing temporal transition of PPI network structures together with serial activation of DRPs associated with transiting networks. This joint estimation enables us to interpret the TDNs in terms of temporal transition of the DRPs. To demonstrate the utility of TEMPI, we applied it to two time-course datasets. TEMPI identified the TDNs that correctly delineated temporal transition of DRPs and time-dependent associations between the DRPs. These TDNs provide hypotheses for mechanisms underlying serial activation of key DRPs and their temporal associations.
  
  
  METHODS
  Source code and sample data files are available at http://sbm.postech.ac.kr/tempi/sources.zip.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Interdisciplinary Bioscience and Bioengineering and Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea and Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Korea.
authors.forename: Yongsoo
authors.initials: Y
authors.lastname: Kim
authors.affiliation: School of Interdisciplinary Bioscience and Bioengineering and Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea and Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Korea.
authors.forename: Jin-Hyeok
authors.initials: JH
authors.lastname: Jang
authors.affiliation: School of Interdisciplinary Bioscience and Bioengineering and Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea and Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Korea.
authors.forename: Seungjin
authors.initials: S
authors.lastname: Choi
authors.affiliation: School of Interdisciplinary Bioscience and Bioengineering and Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea and Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Korea School of Interdisciplinary Bioscience and Bioengineering and Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea and Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Korea.
authors.forename: Daehee
authors.initials: D
authors.lastname: Hwang
mesh_terms: D002453:Cell Cycle; D015870:Gene Expression; D015233:Models, Statistical; D025941:Protein Interaction Mapping / Q000379:methods*