StrongestPath: a Cytoscape application for protein–protein interaction analysis

Background StrongestPath is a Cytoscape 3 application that enables to look for one or more cascades of interactions connecting two single or groups of proteins in a collection of protein-protein interaction (PPI) network or signaling network databases. When there are different levels of confidence over the interactions, it is able to process them and identify the cascade of interactions having the highest total confidence score. Given a set of proteins, StrongestPath can extract and show the network of interactions among them from the given databases, and expand the network by adding new proteins having the most interactions with highest total confidence to the current proteins. The application can also identify any activation or inhibition regulatory paths between two distinct sets of transcription factors and target genes. This application can be either used with a set of built-in human and mouse PPI or signaling databases, or any user-provided database for some organism. Results Our results on 12 signaling pathways from the NetPath database demonstrate that the application can be used for indicating proteins which may play significant roles in the middle of the pathway by finding the strongest path(s) in the PPI or signaling network. Conclusion Easy access to multiple public large databases, generating output in a short time, addressing some key challenges in one platform and providing a user-friendly graphical interface make the StrongestPath easy to use.

[1]  T. M. Murali,et al.  The PathLinker app: Connect the dots in protein interaction networks , 2017, F1000Research.

[2]  Damian Szklarczyk,et al.  The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored , 2010, Nucleic Acids Res..

[3]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[4]  Thomas Zichner,et al.  FASPAD: fast signaling pathway detection , 2007, Bioinform..

[5]  María Martín,et al.  UniProt: A hub for protein information , 2015 .

[6]  Gary D Bader,et al.  NetPath: a public resource of curated signal transduction pathways , 2010, Genome Biology.

[7]  Lincoln Stein,et al.  Reactome: a database of reactions, pathways and biological processes , 2010, Nucleic Acids Res..

[8]  The Uniprot Consortium,et al.  UniProt: a hub for protein information , 2014, Nucleic Acids Res..

[9]  Floyd-Warshall Finding the shortest path with PesCa : a tool for network reconstruction , 2017 .

[10]  Dennis B. Troup,et al.  NCBI GEO: mining tens of millions of expression profiles—database and tools update , 2006, Nucleic Acids Res..

[11]  Gary D. Bader,et al.  NetSlim: high-confidence curated signaling maps , 2011, Database J. Biol. Databases Curation.

[12]  Trey Ideker,et al.  Cytoscape 2.8: new features for data integration and network visualization , 2010, Bioinform..

[13]  Helga Thorvaldsdóttir,et al.  Molecular signatures database (MSigDB) 3.0 , 2011, Bioinform..

[14]  Yosvany López,et al.  HitPredict version 4: comprehensive reliability scoring of physical protein–protein interactions from more than 100 species , 2015, Database J. Biol. Databases Curation.

[15]  Martin H. Schaefer,et al.  HIPPIE v2.0: enhancing meaningfulness and reliability of protein–protein interaction networks , 2016, Nucleic Acids Res..

[16]  Hyojin Kim,et al.  TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions , 2017, Nucleic Acids Res..

[17]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

[18]  Martin Steffen,et al.  Automated modelling of signal transduction networks , 2002, BMC Bioinformatics.