title: Synergy Maps: exploring compound combinations using network-based visualization.
abstract: BACKGROUND
  The phenomenon of super-additivity of biological response to compounds applied jointly, termed synergy, has the potential to provide many therapeutic benefits. Therefore, high throughput screening of compound combinations has recently received a great deal of attention. Large compound libraries and the feasibility of all-pairs screening can easily generate large, information-rich datasets. Previously, these datasets have been visualized using either a heat-map or a network approach-however these visualizations only partially represent the information encoded in the dataset.
  
  
  RESULTS
  A new visualization technique for pairwise combination screening data, termed "Synergy Maps", is presented. In a Synergy Map, information about the synergistic interactions of compounds is integrated with information about their properties (chemical structure, physicochemical properties, bioactivity profiles) to produce a single visualization. As a result the relationships between compound and combination properties may be investigated simultaneously, and thus may afford insight into the synergy observed in the screen. An interactive web app implementation, available at http://richlewis42.github.io/synergy-maps, has been developed for public use, which may find use in navigating and filtering larger scale combination datasets. This tool is applied to a recent all-pairs dataset of anti-malarials, tested against Plasmodium falciparum, and a preliminary analysis is given as an example, illustrating the disproportionate synergism of histone deacetylase inhibitors previously described in literature, as well as suggesting new hypotheses for future investigation.
  
  
  CONCLUSIONS
  Synergy Maps improve the state of the art in compound combination visualization, by simultaneously representing individual compound properties and their interactions. The web-based tool allows straightforward exploration of combination data, and easier identification of correlations between compound properties and interactions.
authors.affiliation: Department of Chemistry, Centre for Molecular Informatics, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW UK.
authors.forename: Richard
authors.identifier: 0000-0001-6642-5771
authors.initials: R
authors.lastname: Lewis
authors.affiliation: National Center for Advancing Translational Sciences, 9800 Medical Center Drive, Rockville, MD 20850 USA.
authors.forename: Rajarshi
authors.initials: R
authors.lastname: Guha
authors.affiliation: TGAC, The Genome Analysis Centre, Norwich Research Park, Norwich, UK ; Gut Health and Food Safety Programme, Institute of Food Research, Norwich Research Park, Norwich, UK.
authors.forename: Tamás
authors.initials: T
authors.lastname: Korcsmaros
authors.affiliation: Department of Chemistry, Centre for Molecular Informatics, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW UK.
authors.forename: Andreas
authors.initials: A
authors.lastname: Bender
keywords: Compound combinations; Dimensionality reduction; Mixtures; Network; Synergy; Visualization