Unified Alignment of Protein-Protein Interaction Networks

Abstract Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfer annotations. However, due to the computational i...

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Autores principales:	Noël Malod-Dognin, Kristina Ban, Nataša Pržulj
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8f438089094d4a76bad0b44343da244b
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spelling	oai:doaj.org-article:8f438089094d4a76bad0b44343da244b2021-12-02T11:52:31ZUnified Alignment of Protein-Protein Interaction Networks10.1038/s41598-017-01085-92045-2322https://doaj.org/article/8f438089094d4a76bad0b44343da244b2017-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-01085-9https://doaj.org/toc/2045-2322Abstract Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfer annotations. However, due to the computational intractability of the network alignment problem, aligners are heuristics providing divergent solutions and no consensus exists on a gold standard, or which scoring scheme should be used to evaluate them. We comprehensively evaluate the alignment scoring schemes and global network aligners on large scale PPI data and observe that three methods, HUBALIGN, L-GRAAL and NATALIE, regularly produce the most topologically and biologically coherent alignments. We study the collective behaviour of network aligners and observe that PPI networks are almost entirely aligned with a handful of aligners that we unify into a new tool, Ulign. Ulign enables complete alignment of two networks, which traditional global and local aligners fail to do. Also, multiple mappings of Ulign define biologically relevant soft clusterings of proteins in PPI networks, which may be used for refining the transfer of annotations across networks. Hence, PPI networks are already well investigated by current aligners, so to gain additional biological insights, a paradigm shift is needed. We propose such a shift come from aligning all available data types collectively rather than any particular data type in isolation from others.Noël Malod-DogninKristina BanNataša PržuljNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Noël Malod-Dognin Kristina Ban Nataša Pržulj Unified Alignment of Protein-Protein Interaction Networks
description	Abstract Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfer annotations. However, due to the computational intractability of the network alignment problem, aligners are heuristics providing divergent solutions and no consensus exists on a gold standard, or which scoring scheme should be used to evaluate them. We comprehensively evaluate the alignment scoring schemes and global network aligners on large scale PPI data and observe that three methods, HUBALIGN, L-GRAAL and NATALIE, regularly produce the most topologically and biologically coherent alignments. We study the collective behaviour of network aligners and observe that PPI networks are almost entirely aligned with a handful of aligners that we unify into a new tool, Ulign. Ulign enables complete alignment of two networks, which traditional global and local aligners fail to do. Also, multiple mappings of Ulign define biologically relevant soft clusterings of proteins in PPI networks, which may be used for refining the transfer of annotations across networks. Hence, PPI networks are already well investigated by current aligners, so to gain additional biological insights, a paradigm shift is needed. We propose such a shift come from aligning all available data types collectively rather than any particular data type in isolation from others.
format	article
author	Noël Malod-Dognin Kristina Ban Nataša Pržulj
author_facet	Noël Malod-Dognin Kristina Ban Nataša Pržulj
author_sort	Noël Malod-Dognin
title	Unified Alignment of Protein-Protein Interaction Networks
title_short	Unified Alignment of Protein-Protein Interaction Networks
title_full	Unified Alignment of Protein-Protein Interaction Networks
title_fullStr	Unified Alignment of Protein-Protein Interaction Networks
title_full_unstemmed	Unified Alignment of Protein-Protein Interaction Networks
title_sort	unified alignment of protein-protein interaction networks
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/8f438089094d4a76bad0b44343da244b
work_keys_str_mv	AT noelmaloddognin unifiedalignmentofproteinproteininteractionnetworks AT kristinaban unifiedalignmentofproteinproteininteractionnetworks AT natasaprzulj unifiedalignmentofproteinproteininteractionnetworks
_version_	1718394995654787072

Unified Alignment of Protein-Protein Interaction Networks

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