title: Inferring domain-domain interactions from protein-protein interactions with formal concept analysis.
abstract: 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.
authors.affiliation: Department of Computer Science, Memorial University of Newfoundland, St John's, Newfoundland and Labrador, Canada.
authors.forename: Susan
authors.initials: S
authors.lastname: Khor
mesh_terms: D000818:Animals; D001412:Bacillus subtilis / Q000378:metabolism; D001669:Biochemical Phenomena; D017173:Caenorhabditis elegans / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein / Q000706:statistics & numerical data; D004331:Drosophila melanogaster / Q000378:metabolism; D006801:Humans; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000378:metabolism; D012568:Schizosaccharomyces / Q000378:metabolism
chemical_list: D011506:Proteins