Integrating protein localization with automated signaling pathway reconstruction
| dc.contributor.author | Youssef, Ibrahim | en |
| dc.contributor.author | Law, Jeffrey N. | en |
| dc.contributor.author | Ritz, Anna | en |
| dc.date.accessioned | 2019-12-16T13:53:06Z | en |
| dc.date.available | 2019-12-16T13:53:06Z | en |
| dc.date.issued | 2019-12-02 | en |
| dc.date.updated | 2019-12-08T04:22:01Z | en |
| dc.description.abstract | Background Understanding cellular responses via signal transduction is a core focus in systems biology. Tools to automatically reconstruct signaling pathways from protein-protein interactions (PPIs) can help biologists generate testable hypotheses about signaling. However, automatic reconstruction of signaling pathways suffers from many interactions with the same confidence score leading to many equally good candidates. Further, some reconstructions are biologically misleading due to ignoring protein localization information. Results We propose LocPL, a method to improve the automatic reconstruction of signaling pathways from PPIs by incorporating information about protein localization in the reconstructions. The method relies on a dynamic program to ensure that the proteins in a reconstruction are localized in cellular compartments that are consistent with signal transduction from the membrane to the nucleus. LocPL and existing reconstruction algorithms are applied to two PPI networks and assessed using both global and local definitions of accuracy. LocPL produces more accurate and biologically meaningful reconstructions on a versatile set of signaling pathways. Conclusion LocPL is a powerful tool to automatically reconstruct signaling pathways from PPIs that leverages cellular localization information about proteins. The underlying dynamic program and signaling model are flexible enough to study cellular signaling under different settings of signaling flow across the cellular compartments. | en |
| dc.description.version | Published version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | BMC Bioinformatics. 2019 Dec 02;20(Suppl 16):505 | en |
| dc.identifier.doi | https://doi.org/10.1186/s12859-019-3077-x | en |
| dc.identifier.uri | http://hdl.handle.net/10919/95991 | en |
| dc.language.iso | en | en |
| dc.rights | Creative Commons Attribution 4.0 International | en |
| dc.rights.holder | The Author(s) | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
| dc.title | Integrating protein localization with automated signaling pathway reconstruction | en |
| dc.title.serial | BMC Bioinformatics | en |
| dc.type | Article - Refereed | en |
| dc.type.dcmitype | Text | en |