Biomine: A Network-Structured Resource of Biological Entities for Link Prediction
- Lauri EronenAffiliated withCarnegie Mellon UniversityDepartment of Computer Science and HIIT, University of Helsinki
- , Petteri HintsanenAffiliated withCarnegie Mellon UniversityDepartment of Computer Science and HIIT, University of Helsinki
- , Hannu ToivonenAffiliated withCarnegie Mellon UniversityDepartment of Computer Science and HIIT, University of Helsinki
Biomine is a biological graph database constructed from public databases. Its entities (vertices) include biological concepts (such as genes, proteins, tissues, processes and phenotypes, as well as scientific articles) and relations (edges) between these entities correspond to real-world phenomena such as “a gene codes for a protein” or “an article refers to a phenotype”. Biomine also provides tools for querying the graph for connections and visualizing them interactively.
We describe the Biomine graph database. We also discuss link discovery in such biological graphs and review possible link prediction measures. Biomine currently contains over 1 million entities and over 8 million relations between them, with focus on human genetics. It is available on-line and can be queried for connecting subgraphs between biological entities.
- Biomine: A Network-Structured Resource of Biological Entities for Link Prediction
- Open Access
- Available under Open Access This content is freely available online to anyone, anywhere at any time.
- Book Title
- Bisociative Knowledge Discovery
- Book Subtitle
- An Introduction to Concept, Algorithms, Tools, and Applications
- Book Part
- Part V
- pp 364-378
- Print ISBN
- Online ISBN
- Series Title
- Lecture Notes in Computer Science
- Series Volume
- Series ISSN
- Springer Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
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