Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/105731
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Computing | - |
dc.creator | Nakajima, N | - |
dc.creator | Hayashida, M | - |
dc.creator | Jansson, J | - |
dc.creator | Maruyama, O | - |
dc.creator | Akutsu, T | - |
dc.date.accessioned | 2024-04-15T07:36:17Z | - |
dc.date.available | 2024-04-15T07:36:17Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/105731 | - |
dc.language.iso | en | en_US |
dc.publisher | Public Library of Science, | en_US |
dc.rights | © 2018 Nakajima et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | en_US |
dc.rights | The following publication Nakajima N, Hayashida M, Jansson J, Maruyama O, Akutsu T (2018) Determining the minimum number of protein-protein interactions required to support known protein complexes. PLoS ONE 13(4): e0195545 is available at https://doi.org/10.1371/journal.pone.0195545. | en_US |
dc.title | Determining the minimum number of protein-protein interactions required to support known protein complexes | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 13 | - |
dc.identifier.issue | 4 | - |
dc.identifier.doi | 10.1371/journal.pone.0195545 | - |
dcterms.abstract | The prediction of protein complexes from protein-protein interactions (PPIs) is a well-studied problem in bioinformatics. However, the currently available PPI data is not enough to describe all known protein complexes. In this paper, we express the problem of determining the minimum number of (additional) required protein-protein interactions as a graph theoretic problem under the constraint that each complex constitutes a connected component in a PPI network. For this problem, we develop two computational methods: one is based on integer linear programming (ILPMinPPI) and the other one is based on an existing greedy-type approximation algorithm (GreedyMinPPI) originally developed in the context of communication and social networks. Since the former method is only applicable to datasets of small size, we apply the latter method to a combination of the CYC2008 protein complex dataset and each of eight PPI datasets (STRING, MINT, BioGRID, IntAct, DIP, BIND, WI-PHI, iRefIndex). The results show that the minimum number of additional required PPIs ranges from 51 (STRING) to 964 (BIND), and that even the four best PPI databases, STRING (51), BioGRID (67), WI-PHI (93) and iRefIndex (85), do not include enough PPIs to form all CYC2008 protein complexes. We also demonstrate that the proposed problem framework and our solutions can enhance the prediction accuracy of existing PPI prediction methods. ILPMinPPI can be freely downloaded from http://sunflower.kuicr.kyoto-u.ac.jp/~nakajima/. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | PLoS ONE, 2018, v. 13, no. 4, e0195545 | - |
dcterms.isPartOf | PLoS one | - |
dcterms.issued | 2018 | - |
dc.identifier.scopus | 2-s2.0-85046009344 | - |
dc.identifier.pmid | 29698482 | - |
dc.identifier.eissn | 1932-6203 | - |
dc.identifier.artn | e0195545 | - |
dc.description.validate | 202402 bcch | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | COMP-1656 | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | Kyoto University, Japan | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 20020475 | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Nakajima_Determining_Minimum_Number.pdf | 3.12 MB | Adobe PDF | View/Open |
Page views
10
Citations as of Jun 30, 2024
Downloads
1
Citations as of Jun 30, 2024
SCOPUSTM
Citations
13
Citations as of Jul 4, 2024
WEB OF SCIENCETM
Citations
9
Citations as of Jul 4, 2024
![](/image/google_scholar.jpg)
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.