Automating the PathLinker app for Cytoscape

Li Jun Huang; Jeffrey N Law; T M Murali

doi:10.12688/f1000research.14616.1

Automating the PathLinker app for Cytoscape

F1000Res. 2018 Jun 12:7:727. doi: 10.12688/f1000research.14616.1. eCollection 2018.

Authors

Li Jun Huang¹, Jeffrey N Law², T M Murali^{1

3}

Affiliations

¹ Department of Computer Science, Virginia Tech, Blacksburg, VA, 24061, USA.
² Genetics, Bioinformatics, and Computational Biology Ph.D. program, Virginia Tech, Blacksburg, VA, 24061, USA.
³ ICTAS Center for Systems Biology of Engineered Tissues, Virginia Tech, Blacksburg, VA, 24061, USA.

Abstract

PathLinker is a graph-theoretic algorithm originally developed to reconstruct the interactions in a signaling pathway of interest. It efficiently computes multiple short paths within a background protein interaction network from the receptors to transcription factors (TFs) in a pathway. Since December 2015, PathLinker has been available as an app for Cytoscape. This paper describes how we automated the app to use the CyRest infrastructure and how users can incorporate PathLinker into their software pipelines.

Keywords: CyREST API; Network Biology; Pathway Reconstruction; Shortest Paths.

Grants and funding

National Science Foundation grant [CCF-1617678] supported this research. The research is also partially based upon work supported by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via the Army Research Office (ARO) under cooperative Agreement Number [W911NF-17-2-0105]. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the ODNI, IARPA, ARO, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon.