title: Xtalk: a path-based approach for identifying crosstalk between signaling pathways.
abstract: BACKGROUND
  Cells communicate with their environment via signal transduction pathways. On occasion, the activation of one pathway can produce an effect downstream of another pathway, a phenomenon known as crosstalk. Existing computational methods to discover such pathway pairs rely on simple overlap statistics.
  
  
  RESULTS
  We present Xtalk, a path-based approach for identifying pairs of pathways that may crosstalk. Xtalk computes the statistical significance of the average length of multiple short paths that connect receptors in one pathway to the transcription factors in another. By design, Xtalk reports the precise interactions and mechanisms that support the identified crosstalk. We applied Xtalk to signaling pathways in the KEGG and NCI-PID databases. We manually curated a gold standard set of 132 crosstalking pathway pairs and a set of 140 pairs that did not crosstalk, for which Xtalk achieved an area under the receiver operator characteristic curve of 0.65, a 12% improvement over the closest competing approach. The area under the receiver operator characteristic curve varied with the pathway, suggesting that crosstalk should be evaluated on a pathway-by-pathway level. We also analyzed an extended set of 658 pathway pairs in KEGG and to a set of more than 7000 pathway pairs in NCI-PID. For the top-ranking pairs, we found substantial support in the literature (81% for KEGG and 78% for NCI-PID). We provide examples of networks computed by Xtalk that accurately recovered known mechanisms of crosstalk.
  
  
  METHODS
  The XTALK software is available at http://bioinformatics.cs.vt.edu/~murali/software. Crosstalk networks are available at http://graphspace.org/graphs?tags=2015-bioinformatics-xtalk.
  
  
  BACKGROUND
  ategge@vt.edu, murali@cs.vt.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Computer Science, Department of Statistics and.
authors.forename: Allison N
authors.initials: AN
authors.lastname: Tegge
authors.affiliation: Department of Computer Science.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Sharp
authors.affiliation: Department of Computer Science, ICTAS Center for Systems Biology of Engineered Tissues, Virginia Tech, Blacksburg, VA 24061, USA.
authors.forename: T M
authors.initials: TM
authors.lastname: Murali
mesh_terms: D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D006801:Humans; D008954:Models, Biological; D015398:Signal Transduction; D012984:Software; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors