semantic search
metalife trinity » analyzer » semantic search
Key Features:
- integrates broad array of biological entities from multiple proved data sources
- common search gateway suitable for performing simple quests as well as sophisticated inquiries
- elaborate inference machinery for automated conclusions
- natural language and diagrammatical expressive output
Description:
Metalife Semantic Search integrates multiple data sources: from protein and nucleotide sequence databases, through
classification and nomenclature ones, through molecule structure ones, to highly specialized databases.
These include UniProt, PhenomicDB, GenBank, Entrez Gene, GO, PDB, NCBI Taxonomy, Pfam, Enzyme, and RefSeq.
All biological entities from these databases are integrated into a single semantically organized Knowledge Base. This allows searching for connections and relationships between biological objects from different levels of organization of living matter by using an extended biologically oriented ontology.
The key component of the Metalife Semantic Search system is the inferencing of new data interrelations. The underlying rule based inference acts as knowledge generator, meaning that new relationships are established based on a priori defined biological rules. This process might be iterated – relations generated by one rule are automatically subjected as an input of another rule-based iteration.
The semantic data organization, the biologically oriented ontology and the inference machinery all together provide a new approach to the users' search activities. One does not obtain a set of different entries from distinct databases but could examine a semantic network which brings and visualizes together related biological entities from different sources. This facilitates and makes the search more efficient, as well as reveals new relations through the inference.
Metalife Semantic Search provides an integrative approach to search for biological objects' characteristics and find or infer information of interest such as what is their function in relation to other entities.
All biological entities from these databases are integrated into a single semantically organized Knowledge Base. This allows searching for connections and relationships between biological objects from different levels of organization of living matter by using an extended biologically oriented ontology.
The key component of the Metalife Semantic Search system is the inferencing of new data interrelations. The underlying rule based inference acts as knowledge generator, meaning that new relationships are established based on a priori defined biological rules. This process might be iterated – relations generated by one rule are automatically subjected as an input of another rule-based iteration.
The semantic data organization, the biologically oriented ontology and the inference machinery all together provide a new approach to the users' search activities. One does not obtain a set of different entries from distinct databases but could examine a semantic network which brings and visualizes together related biological entities from different sources. This facilitates and makes the search more efficient, as well as reveals new relations through the inference.
Metalife Semantic Search provides an integrative approach to search for biological objects' characteristics and find or infer information of interest such as what is their function in relation to other entities.
Order installation of local copy of Semantic Search!
Metalife offers installation of local copy of its products upon licensing. Ordering a local copy benefits private users with the following extra advantages:
- Data security ensured by the management of all analyses and sources locally in your organization's secured network.
- Impossibility of competitor companies to track down your searches in public resources and reveal your interests.
- Custom development of project specific GUI features, new functionalities, DB sources.
- Completely new decisions implementation upon request.