Biomine: predicting links between biological entities using network models of heterogeneous databases
نویسندگان
چکیده
منابع مشابه
GenXref. VI: Automatic generation of links between two heterogeneous databases
MOTIVATION A large proportion of the information found in public databases is not sufficiently cross-referenced. We developed genXref, an automated system for link inference, because embarking on a manual cross-referencing of genome data would require too much expensive human expertise. It uses information retrieval technology to generate links between objects of heterogeneous databases. RESU...
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data envelopment analysis (dea) is a powerful tool for measuring relative efficiency of organizational units referred to as decision making units (dmus). in most cases dmus have network structures with internal linking activities. traditional dea models, however, consider dmus as black boxes with no regard to their linking activities and therefore do not provide decision makers with the reasons...
Biological Network Representations and Databases
Transcriptional Regulatory Networks. In transcription regulatory networks the nodes represent transcription factors and genes while the links describe regulation-based interactions. Each link is directed, pointing from the transcription factor to the gene that it regulates. To compare the topological properties of transcription-regulatory networks to those of metabolic and protein-protein inter...
متن کاملApplications and Evaluation: Overview
Eronen at al. [1] discusses Biomine as a BisoNet which integrates heterogeneous biological databases. It consists of over 1 million nodes, representing biological entities (genes, proteins, ontology terms, . . . ), and over 8 million edges, representing weighted relations of different types. Biomine search algorithms implement link discovery between distant nodes in the graph, and can be exploi...
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The goal of our research is to predict a relation (predicate) of two given RDF entities (subject and object). Link prediction between entities is important for developing large-scale ontologies and for knowledge graph completion. TransE and TransR have been proposed as the methods for such a prediction. However, TransE and TransR embed both entities and relations in the same (or different) sema...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2012
ISSN: 1471-2105
DOI: 10.1186/1471-2105-13-119