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Ontological visualization of protein-protein interactions.

ABSTRACT: Cellular processes require the interaction of many proteins across several cellular compartments. Determining the collective network of such interactions is an important aspect of understanding the role and regulation of individual proteins. The Gene Ontology (GO) is used by model organism databases and other bioinformatics resources to provide functional annotation of proteins. The annotation process provides a mechanism to document the binding of one protein with another. We have constructed protein interaction networks for mouse proteins utilizing the information encoded in the GO annotations. The work reported here presents a methodology for integrating and visualizing information on protein-protein interactions.GO annotation at Mouse Genome Informatics (MGI) captures 1318 curated, documented interactions. These include 129 binary interactions and 125 interaction involving three or more gene products. Three networks involve over 30 partners, the largest involving 109 proteins. Several tools are available at MGI to visualize and analyze these data.Curators at the MGI database annotate protein-protein interaction data from experimental reports from the literature. Integration of these data with the other types of data curated at MGI places protein binding data into the larger context of mouse biology and facilitates the generation of new biological hypotheses based on physical interactions among gene products.

SUBMITTER: Drabkin HJ

PROVIDER: S-EPMC550656 | biostudies-literature | 2005 Feb

REPOSITORIES: biostudies-literature

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Ontological visualization of protein-protein interactions.

Drabkin Harold J HJ Hollenbeck Christopher C Hill David P DP Blake Judith A JA

BMC bioinformatics 20050211

<h4>Background</h4>Cellular processes require the interaction of many proteins across several cellular compartments. Determining the collective network of such interactions is an important aspect of understanding the role and regulation of individual proteins. The Gene Ontology (GO) is used by model organism databases and other bioinformatics resources to provide functional annotation of proteins. The annotation process provides a mechanism to document the binding of one protein with another. We ...[more]

PMID: 15707487

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Project description:BackgroundThe symbiotic interactions that occur between humans and organisms in our environment have a tremendous impact on our health. Recently, there has been a surge in interest in understanding the complex relationships between the microbiome and human health and host immunity against microbial pathogens, among other things. To collect and manage data about these interactions and their complexity, scientists will need ontologies that represent symbiotic interactions as they occur in reality.MethodsWe began with two papers that reviewed the usage of 'symbiosis' and related terms in the biology and ecology literature and prominent textbooks. We then analyzed several prominent standard terminologies and ontologies that contain representations of symbiotic interactions, to determine if they appropriately defined 'symbiosis' and related terms according to current scientific usage as identified by the review papers. In the process, we identified several subtypes of symbiotic interactions, as well as the characteristics that differentiate them, which we used to propose textual and axiomatic definitions for each subtype of interaction. To both illustrate how to use the ontological representations and definitions we created and provide additional quality assurance on key definitions, we carried out a referent tracking analysis and representation of three scenarios involving symbiotic interactions among organisms.ResultsWe found one definition of 'symbiosis' in an existing ontology that was consistent with the vast preponderance of scientific usage in biology and ecology. However, that ontology changed its definition during the course of our work, and discussions are ongoing. We present a new definition that we have proposed. We also define 34 subtypes of symbiosis. Our referent tracking analysis showed that it is necessary to define symbiotic interactions at the level of the individual, rather than at the species level, due to the complex nature in which organisms can go from participating in one type of symbiosis with one organism to participating in another type of symbiosis with a different organism.ConclusionAs a result of our efforts here, we have developed a robust representation of symbiotic interactions using a realism-based approach, which fills a gap in existing biomedical ontologies.

Dataset Information

Ontological visualization of protein-protein interactions.

Publications

Ontological visualization of protein-protein interactions.

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