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DOMINE: a database of protein domain interactions.

Raghavachari B, Tasneem A, Przytycka TM, Jothi R - Nucleic Acids Res. (2007)

Bottom Line: DOMINE contains a total of 20 513 unique domain-domain interactions among 4036 Pfam domains, out of which 4349 are inferred from PDB entries and 17 781 were predicted by at least one computational approach.This database will serve as a valuable resource to those working in the field of protein and domain interactions.DOMINE may not only serve as a reference to experimentalists who test for new protein and domain interactions, but also offers a consolidated dataset for analysis by bioinformaticians who seek to test ideas regarding the underlying factors that control the topological structure of interaction networks.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, University of Texas at Dallas, Richardson, TX 75083, USA.

ABSTRACT
DOMINE is a database of known and predicted protein domain interactions compiled from a variety of sources. The database contains domain-domain interactions observed in PDB entries, and those that were predicted by eight different computational approaches. DOMINE contains a total of 20 513 unique domain-domain interactions among 4036 Pfam domains, out of which 4349 are inferred from PDB entries and 17 781 were predicted by at least one computational approach. This database will serve as a valuable resource to those working in the field of protein and domain interactions. DOMINE may not only serve as a reference to experimentalists who test for new protein and domain interactions, but also offers a consolidated dataset for analysis by bioinformaticians who seek to test ideas regarding the underlying factors that control the topological structure of interaction networks. DOMINE is freely available at http://domine.utdallas.edu.

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A schematic overview of the DOMINE database.
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Figure 2: A schematic overview of the DOMINE database.

Mentions: Interactions predicted by computational approaches are classified into three categories using a simple classification scheme. Putative interactions predicted by an approach using multiple sources of evidence or those predicted by more than two sufficiently different approaches are considered as high-confidence predictions (HCP). Putative interactions with support from just one approach, but whose constituent domains (hetero) are known to be part of the same biological process (based on GO classification), are considered as medium-confidence predictions (MCP). The rest of the predictions is considered as low-confidence predictions. A schematic overview of the classification is shown in Figure 2. Of the 17 781 predictions, 3143 interactions are HCP (predicted by ME or at least two sufficiently different approaches), 730 interactions are medium-confidence predictions (hetero-domain interactions in which both domains are a part of the same biological process as per GO classification), and the remaining 13 908 are low-confidence predictions. The sets of high-, medium- and low-confidence predictions are enriched with 42.3, 5.8 and 1.8% of known interactions, respectively. The list of 55 predicted domain–domain interactions, confirmed by at least four sufficiently different computational approaches, is given in the Supplementary Table 2.Figure 2.


DOMINE: a database of protein domain interactions.

Raghavachari B, Tasneem A, Przytycka TM, Jothi R - Nucleic Acids Res. (2007)

A schematic overview of the DOMINE database.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2238965&req=5

Figure 2: A schematic overview of the DOMINE database.
Mentions: Interactions predicted by computational approaches are classified into three categories using a simple classification scheme. Putative interactions predicted by an approach using multiple sources of evidence or those predicted by more than two sufficiently different approaches are considered as high-confidence predictions (HCP). Putative interactions with support from just one approach, but whose constituent domains (hetero) are known to be part of the same biological process (based on GO classification), are considered as medium-confidence predictions (MCP). The rest of the predictions is considered as low-confidence predictions. A schematic overview of the classification is shown in Figure 2. Of the 17 781 predictions, 3143 interactions are HCP (predicted by ME or at least two sufficiently different approaches), 730 interactions are medium-confidence predictions (hetero-domain interactions in which both domains are a part of the same biological process as per GO classification), and the remaining 13 908 are low-confidence predictions. The sets of high-, medium- and low-confidence predictions are enriched with 42.3, 5.8 and 1.8% of known interactions, respectively. The list of 55 predicted domain–domain interactions, confirmed by at least four sufficiently different computational approaches, is given in the Supplementary Table 2.Figure 2.

Bottom Line: DOMINE contains a total of 20 513 unique domain-domain interactions among 4036 Pfam domains, out of which 4349 are inferred from PDB entries and 17 781 were predicted by at least one computational approach.This database will serve as a valuable resource to those working in the field of protein and domain interactions.DOMINE may not only serve as a reference to experimentalists who test for new protein and domain interactions, but also offers a consolidated dataset for analysis by bioinformaticians who seek to test ideas regarding the underlying factors that control the topological structure of interaction networks.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, University of Texas at Dallas, Richardson, TX 75083, USA.

ABSTRACT
DOMINE is a database of known and predicted protein domain interactions compiled from a variety of sources. The database contains domain-domain interactions observed in PDB entries, and those that were predicted by eight different computational approaches. DOMINE contains a total of 20 513 unique domain-domain interactions among 4036 Pfam domains, out of which 4349 are inferred from PDB entries and 17 781 were predicted by at least one computational approach. This database will serve as a valuable resource to those working in the field of protein and domain interactions. DOMINE may not only serve as a reference to experimentalists who test for new protein and domain interactions, but also offers a consolidated dataset for analysis by bioinformaticians who seek to test ideas regarding the underlying factors that control the topological structure of interaction networks. DOMINE is freely available at http://domine.utdallas.edu.

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