Protein-to-protein interactions: Technologies, databases, and algorithms
ACM Computing Surveys (CSUR)
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Protein-protein interaction (PPI) data are often stored in publicly available databases that are often queried by the use of simple query interfaces allowing only key-based queries. Such databases enable the retrieval of one or more proteins that interact with a target protein, using a target protein identifier. Nevertheless, a lot of biological information is available and is spread on different sources and encoded in different ontologies (e.g. Gene Ontology). Annotating existing PPI databases with biological information may result in richer querying interfaces and successively could enable the development of novel algorithms that may use biological information. The OntoPIN project showed the effectiveness of the introduction of a framework for the ontology-based management and querying of Protein-Protein Interaction Data. The OntoPIN framework first merges PPI data with annotations extracted from existing ontologies (e.g. Gene Ontology) and stores annotated data into a database. Then, a semantic-based query interface enables users to query these data by using biological concepts. OntoPIN allows: (a) to extend existing PPI databases by using ontologies, (b) to enable a key-based querying of annotated data, and (c) to offer a novel query interface based on semantic similarity among annotations. This paper presents the current state of the OntoPIN project discussing a case study on human protein interaction data.