IMMAN : an R/Bioconductor package for Interolog protein network reconstruction, mapping and mining analysis

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http://hdl.handle.net/10138/300214

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Ashtiani , M , Nickchi , P , Jahangiri-Tazehkand , S , Safari , A , Mirzaie , M & Jafari , M 2019 , ' IMMAN : an R/Bioconductor package for Interolog protein network reconstruction, mapping and mining analysis ' , BMC Bioinformatics , vol. 20 , 73 . https://doi.org/10.1186/s12859-019-2659-y

Title: IMMAN : an R/Bioconductor package for Interolog protein network reconstruction, mapping and mining analysis
Author: Ashtiani, Minoo; Nickchi, Payman; Jahangiri-Tazehkand, Soheil; Safari, Abdollah; Mirzaie, Mehdi; Jafari, Mohieddin
Contributor: University of Helsinki, Institute for Molecular Medicine Finland
Date: 2019-02-12
Language: eng
Number of pages: 4
Belongs to series: BMC Bioinformatics
ISSN: 1471-2105
URI: http://hdl.handle.net/10138/300214
Abstract: Background: Reconstruction of protein-protein interaction networks (PPIN) has been riddled with controversy for decades. Particularly, false-negative and - positive interactions make this progress even more complicated. Also, lack of a standard PPIN limits us in the comparison studies and results in the incompatible outcomes. Using an evolution-based concept, i.e. interolog which refers to interacting orthologous protein sets, pave the way toward an optimal benchmark. Results: Here, we provide an R package, IMMAN, as a tool for reconstructing Interolog Protein Network (IPN) by integrating several Protein-protein Interaction Networks (PPINs). Users can unify different PPINs to mine conserved common networks among species. IMMAN is designed to retrieve IPNs with different degrees of conservation to engage prediction analysis of protein functions according to their networks. Conclusions: IPN consists of evolutionarily conserved nodes and their related edges regarding low false positive rates, which can be considered as a gold standard network in the contexts of biological network analysis regarding to those PPINs which is derived from.
Subject: Protein-protein interaction networks (PPINs)
Interolog protein network (IPN)
Bioconductor
Network biology
INTEGRATION
PREDICTION
1182 Biochemistry, cell and molecular biology
111 Mathematics
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