Inferring domain-domain interactions from protein-protein interactions with formal concept analysis.
Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2014-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24586450/?tool=EBI |
| _version_ | 1818701620723056640 |
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| author | Susan Khor |
| author_facet | Susan Khor |
| author_sort | Susan Khor |
| collection | DOAJ |
| description | Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains. |
| first_indexed | 2024-12-17T15:23:44Z |
| format | Article |
| id | doaj.art-168c3c70b2aa4554acb6a6f0f68ac31f |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-17T15:23:44Z |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-168c3c70b2aa4554acb6a6f0f68ac31f2022-12-21T21:43:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0192e8894310.1371/journal.pone.0088943Inferring domain-domain interactions from protein-protein interactions with formal concept analysis.Susan KhorIdentifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24586450/?tool=EBI |
| spellingShingle | Susan Khor Inferring domain-domain interactions from protein-protein interactions with formal concept analysis. PLoS ONE |
| title | Inferring domain-domain interactions from protein-protein interactions with formal concept analysis. |
| title_full | Inferring domain-domain interactions from protein-protein interactions with formal concept analysis. |
| title_fullStr | Inferring domain-domain interactions from protein-protein interactions with formal concept analysis. |
| title_full_unstemmed | Inferring domain-domain interactions from protein-protein interactions with formal concept analysis. |
| title_short | Inferring domain-domain interactions from protein-protein interactions with formal concept analysis. |
| title_sort | inferring domain domain interactions from protein protein interactions with formal concept analysis |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24586450/?tool=EBI |
| work_keys_str_mv | AT susankhor inferringdomaindomaininteractionsfromproteinproteininteractionswithformalconceptanalysis |