scholarly journals IMMAN: an R/Bioconductor package for Interolog protein network reconstruction, Mapping and Mining ANalysis

2016 ◽  
Author(s):  
Minoo Ashtinai ◽  
Payman Nickchi ◽  
Soheil Jahangiri-Tazehkand ◽  
Abdollah Safari ◽  
Mehdi Mirzaie ◽  
...  
Keyword(s):  
Protein Function ◽  
Protein Function Prediction ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Protein Network ◽  
Supplementary Information ◽  
Protein Protein Interaction ◽  
Link Type ◽  
Supplementary Material ◽  
Protein Protein Interaction Networks

SummaryIMMAN is a software for reconstructing Interolog Protein Network (IPN) by integrating several Protein-protein Interaction Networks (PPIN). Users can unify different PPINs to mine conserved common network among species. IMMAN helps to retrieve IPNs with different degrees of conservation to engage for protein function prediction analysis based on protein networks.AvailabilityIMMAN is freely available at https://bioconductor.org/packages/IMMAN, http://profiles.bs.ipm.ir/softwares/IMMAN/[email protected], [email protected], [email protected] informationSupplementary data are available online.

scholarly journals AligNet: alignment of protein-protein interaction networks

2020 ◽  
Vol 21 (S6) ◽  
Author(s):  
Adrià Alcalá ◽  
Ricardo Alberich ◽  
Mercè Llabrés ◽  
Francesc Rosselló ◽  
Gabriel Valiente
Keyword(s):  
Protein Interaction ◽  
Protein Function ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Alignment Algorithm ◽  
Good Balance ◽  
Protein Protein Interaction ◽  
Functional Relations ◽  
Protein Protein Interaction Networks ◽  
Molecular Functions

Abstract Background All molecular functions and biological processes are carried out by groups of proteins that interact with each other. Metaproteomic data continuously generates new proteins whose molecular functions and relations must be discovered. A widely accepted structure to model functional relations between proteins are protein-protein interaction networks (PPIN), and their analysis and alignment has become a key ingredient in the study and prediction of protein-protein interactions, protein function, and evolutionary conserved assembly pathways of protein complexes. Several PPIN aligners have been proposed, but attaining the right balance between network topology and biological information is one of the most difficult and key points in the design of any PPIN alignment algorithm. Results Motivated by the challenge of well-balanced and efficient algorithms, we have designed and implemented AligNet, a parameter-free pairwise PPIN alignment algorithm aimed at bridging the gap between topologically efficient and biologically meaningful matchings. A comparison of the results obtained with AligNet and with the best aligners shows that AligNet achieves indeed a good balance between topological and biological matching. Conclusion In this paper we present AligNet, a new pairwise global PPIN aligner that produces biologically meaningful alignments, by achieving a good balance between structural matching and protein function conservation, and more efficient computations than state-of-the-art tools.

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