title: Predicting receptor-ligand pairs through kernel learning.
abstract: BACKGROUND
  Regulation of cellular events is, often, initiated via extracellular signaling. Extracellular signaling occurs when a circulating ligand interacts with one or more membrane-bound receptors. Identification of receptor-ligand pairs is thus an important and specific form of PPI prediction.
  
  
  RESULTS
  Given a set of disparate data sources (expression data, domain content, and phylogenetic profile) we seek to predict new receptor-ligand pairs. We create a combined kernel classifier and assess its performance with respect to the Database of Ligand-Receptor Partners (DLRP) 'golden standard' as well as the method proposed by Gertz et al. Among our findings, we discover that our predictions for the tgfβ family accurately reconstruct over 76% of the supported edges (0.76 recall and 0.67 precision) of the receptor-ligand bipartite graph defined by the DLRP "golden standard". In addition, for the tgfβ family, the combined kernel classifier is able to relatively improve upon the Gertz et al. work by a factor of approximately 1.5 when considering that our method has an F-measure of 0.71 while that of Gertz et al. has a value of 0.48.
  
  
  CONCLUSIONS
  The prediction of receptor-ligand pairings is a difficult and complex task. We have demonstrated that using kernel learning on multiple data sources provides a stronger alternative to the existing method in solving this task.
authors.affiliation: SCD-ESAT, Department of Electrical Engineering, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, Leuven 3001, Belgium.
authors.forename: Ernesto
authors.initials: E
authors.lastname: Iacucci
authors.forename: Fabian
authors.initials: F
authors.lastname: Ojeda
authors.forename: Bart
authors.initials: B
authors.lastname: De Moor
authors.forename: Yves
authors.initials: Y
authors.lastname: Moreau
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D030562:Databases, Protein; D006801:Humans; D008024:Ligands; D010802:Phylogeny; D011485:Protein Binding; D025941:Protein Interaction Mapping; D011956:Receptors, Cell Surface / Q000378:metabolism*; D015398:Signal Transduction; D012984:Software
chemical_list: D008024:Ligands; D011956:Receptors, Cell Surface