RocSampler: regularizing overlapping protein complexes in protein-protein interaction networks
Abstract Background In recent years, protein-protein interaction (PPI) networks have been well recognized as important resources to elucidate various biological processes and cellular mechanisms. In this paper, we address the problem of predicting protein complexes from a PPI network. This problem h...
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| Format: | Article |
| Language: | English |
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BMC
2017-12-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-017-1920-5 |
| _version_ | 1818339752726757376 |
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| author | Osamu Maruyama Yuki Kuwahara |
| author_facet | Osamu Maruyama Yuki Kuwahara |
| author_sort | Osamu Maruyama |
| collection | DOAJ |
| description | Abstract Background In recent years, protein-protein interaction (PPI) networks have been well recognized as important resources to elucidate various biological processes and cellular mechanisms. In this paper, we address the problem of predicting protein complexes from a PPI network. This problem has two difficulties. One is related to small complexes, which contains two or three components. It is relatively difficult to identify them due to their simpler internal structure, but unfortunately complexes of such sizes are dominant in major protein complex databases, such as CYC2008. Another difficulty is how to model overlaps between predicted complexes, that is, how to evaluate different predicted complexes sharing common proteins because CYC2008 and other databases include such protein complexes. Thus, it is critical how to model overlaps between predicted complexes to identify them simultaneously. Results In this paper, we propose a sampling-based protein complex prediction method, RocSampler (Regularizing Overlapping Complexes), which exploits, as part of the whole scoring function, a regularization term for the overlaps of predicted complexes and that for the distribution of sizes of predicted complexes. We have implemented RocSampler in MATLAB and its executable file for Windows is available at the site, http://imi.kyushu-u.ac.jp/~om/software/RocSampler/ . Conclusions We have applied RocSampler to five yeast PPI networks and shown that it is superior to other existing methods. This implies that the design of scoring functions including regularization terms is an effective approach for protein complex prediction. |
| first_indexed | 2024-12-13T15:32:00Z |
| format | Article |
| id | doaj.art-a03016e1a72441e7923a3e5e08ec2ba7 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-13T15:32:00Z |
| publishDate | 2017-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-a03016e1a72441e7923a3e5e08ec2ba72022-12-21T23:40:09ZengBMCBMC Bioinformatics1471-21052017-12-0118S15516210.1186/s12859-017-1920-5RocSampler: regularizing overlapping protein complexes in protein-protein interaction networksOsamu Maruyama0Yuki Kuwahara1Institute of Mathematics for Industry, Kyushu UniversityGraduate School of Mathematics, Kyushu UniversityAbstract Background In recent years, protein-protein interaction (PPI) networks have been well recognized as important resources to elucidate various biological processes and cellular mechanisms. In this paper, we address the problem of predicting protein complexes from a PPI network. This problem has two difficulties. One is related to small complexes, which contains two or three components. It is relatively difficult to identify them due to their simpler internal structure, but unfortunately complexes of such sizes are dominant in major protein complex databases, such as CYC2008. Another difficulty is how to model overlaps between predicted complexes, that is, how to evaluate different predicted complexes sharing common proteins because CYC2008 and other databases include such protein complexes. Thus, it is critical how to model overlaps between predicted complexes to identify them simultaneously. Results In this paper, we propose a sampling-based protein complex prediction method, RocSampler (Regularizing Overlapping Complexes), which exploits, as part of the whole scoring function, a regularization term for the overlaps of predicted complexes and that for the distribution of sizes of predicted complexes. We have implemented RocSampler in MATLAB and its executable file for Windows is available at the site, http://imi.kyushu-u.ac.jp/~om/software/RocSampler/ . Conclusions We have applied RocSampler to five yeast PPI networks and shown that it is superior to other existing methods. This implies that the design of scoring functions including regularization terms is an effective approach for protein complex prediction.http://link.springer.com/article/10.1186/s12859-017-1920-5Protein-protein interactionProtein complexMarkov chain Monte CarloRocSamplerRegularization term |
| spellingShingle | Osamu Maruyama Yuki Kuwahara RocSampler: regularizing overlapping protein complexes in protein-protein interaction networks BMC Bioinformatics Protein-protein interaction Protein complex Markov chain Monte Carlo RocSampler Regularization term |
| title | RocSampler: regularizing overlapping protein complexes in protein-protein interaction networks |
| title_full | RocSampler: regularizing overlapping protein complexes in protein-protein interaction networks |
| title_fullStr | RocSampler: regularizing overlapping protein complexes in protein-protein interaction networks |
| title_full_unstemmed | RocSampler: regularizing overlapping protein complexes in protein-protein interaction networks |
| title_short | RocSampler: regularizing overlapping protein complexes in protein-protein interaction networks |
| title_sort | rocsampler regularizing overlapping protein complexes in protein protein interaction networks |
| topic | Protein-protein interaction Protein complex Markov chain Monte Carlo RocSampler Regularization term |
| url | http://link.springer.com/article/10.1186/s12859-017-1920-5 |
| work_keys_str_mv | AT osamumaruyama rocsamplerregularizingoverlappingproteincomplexesinproteinproteininteractionnetworks AT yukikuwahara rocsamplerregularizingoverlappingproteincomplexesinproteinproteininteractionnetworks |