title: pwOmics: an R package for pathway-based integration of time-series omics data using public database knowledge.
abstract: Characterization of biological processes is progressively enabled with the increased generation of omics data on different signaling levels. Here we present a straightforward approach for the integrative analysis of data from different high-throughput technologies based on pathway and interaction models from public databases. pwOmics performs pathway-based level-specific data comparison of coupled human proteomic and genomic/transcriptomic datasets based on their log fold changes. Separate downstream and upstream analyses results on the functional levels of pathways, transcription factors and genes/transcripts are performed in the cross-platform consensus analysis. These provide a basis for the combined interpretation of regulatory effects over time. Via network reconstruction and inference methods (Steiner tree, dynamic Bayesian network inference) consensus graphical networks can be generated for further analyses and visualization.
  
  
  METHODS
  The R package pwOmics is freely available on Bioconductor (http://www.bioconductor.org/).
  
  
  BACKGROUND
  astrid.wachter@med.uni-goettingen.de.
authors.affiliation: Department of Medical Statistics, Georg-August-University Göttingen, Germany.
authors.forename: Astrid
authors.initials: A
authors.lastname: Wachter
authors.affiliation: Department of Medical Statistics, Georg-August-University Göttingen, Germany.
authors.forename: Tim
authors.initials: T
authors.lastname: Beißbarth
mesh_terms: D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D023281:Genomics / Q000379:methods*; D006801:Humans; D040901:Proteomics / Q000379:methods*; D015398:Signal Transduction; D012984:Software; D013997:Time Factors