Literature DB >> 26336140

Global Alignment of Protein-Protein Interaction Networks: A Survey.

Ahed Elmsallati, Connor Clark, Jugal Kalita.   

Abstract

In this paper, we survey algorithms that perform global alignment of networks or graphs. Global network alignment aligns two or more given networks to find the best mapping from nodes in one network to nodes in other networks. Since graphs are a common method of data representation, graph alignment has become important with many significant applications. Protein-protein interactions can be modeled as networks and aligning these networks of protein interactions has many applications in biological research. In this survey, we review algorithms for global pairwise alignment highlighting various proposed approaches, and classify them based on their methodology. Evaluation metrics that are used to measure the quality of the resulting alignments are also surveyed. We discuss and present a comparison between selected aligners on the same datasets and evaluate using the same evaluation metrics. Finally, a quick overview of the most popular databases of protein interaction networks is presented focusing on datasets that have been used recently.

Mesh:

Year:  2015        PMID: 26336140     DOI: 10.1109/TCBB.2015.2474391

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  10 in total

1.  Matchability of heterogeneous networks pairs.

Authors:  Vince Lyzinski; Daniel L Sussman
Journal:  Inf inference       Date:  2020-01-06

2.  From homogeneous to heterogeneous network alignment via colored graphlets.

Authors:  Shawn Gu; John Johnson; Fazle E Faisal; Tijana Milenković
Journal:  Sci Rep       Date:  2018-08-21       Impact factor: 4.379

3.  Pairwise Versus Multiple Global Network Alignment.

Authors:  Vipin Vijayan; Shawn Gu; Eric T Krebs; Lei Meng; Tijana MilenkoviĆ
Journal:  IEEE Access       Date:  2020-02-27       Impact factor: 3.367

4.  Data-driven network alignment.

Authors:  Shawn Gu; Tijana Milenković
Journal:  PLoS One       Date:  2020-07-02       Impact factor: 3.240

5.  Local versus global biological network alignment.

Authors:  Lei Meng; Aaron Striegel; Tijana Milenković
Journal:  Bioinformatics       Date:  2016-06-29       Impact factor: 6.937

6.  Unified Alignment of Protein-Protein Interaction Networks.

Authors:  Noël Malod-Dognin; Kristina Ban; Nataša Pržulj
Journal:  Sci Rep       Date:  2017-04-19       Impact factor: 4.379

7.  Alignment of dynamic networks.

Authors:  V Vijayan; D Critchlow; T Milenkovic
Journal:  Bioinformatics       Date:  2017-07-15       Impact factor: 6.937

8.  PROPER: global protein interaction network alignment through percolation matching.

Authors:  Ehsan Kazemi; Hamed Hassani; Matthias Grossglauser; Hassan Pezeshgi Modarres
Journal:  BMC Bioinformatics       Date:  2016-12-12       Impact factor: 3.169

9.  ConnectedAlign: a PPI network alignment method for identifying conserved protein complexes across multiple species.

Authors:  Jianliang Gao; Bo Song; Xiaohua Hu; Fengxia Yan; Jianxin Wang
Journal:  BMC Bioinformatics       Date:  2018-08-13       Impact factor: 3.169

10.  AligNet: alignment of protein-protein interaction networks.

Authors:  Adrià Alcalá; Ricardo Alberich; Mercè Llabrés; Francesc Rosselló; Gabriel Valiente
Journal:  BMC Bioinformatics       Date:  2020-11-18       Impact factor: 3.169

  10 in total

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