Not Just Simple “A to B” Relationships
Contextual details such as species specificity, cell type/tissue context, site and type of mutations, direction of change, post-translational modification sites, epigenetic modifications, and experimental methods are included. These contextual details allow you to ask questions such as “transcription factor X increases expression of a gene Y in a specific cell type.”
QIAGEN’s Ingenuity Ontology makes information computationally accessible so you can more rapidly infer novel insights from your own data or get to specific knowledge that is relevant to your research. Ask questions across various types of connections (molecular, cellular, and organismal) and make inferences from one concept to another, or find likely paths between molecular concepts (gene to disease, drug to gene, etc.).
Provides Synonym Resolution
QIAGEN’s Ingenuity Ontology ensures semantic and linguistic consistency across concepts. The Knowledge Base incorporates processes to resolve synonyms and homographs in order to maintain object identity and remove duplicate objects. Because the same terms are mapped across databases and concepts, you can integrate disparate information from unrelated disciplines and sources in order to run powerful queries and get precise answers to complex, data-driven questions. It also allows you to take information from multiple sources and related it to your own dataset or questions of interest.
Content Acquisition consists of a robust set of people, processes and technology for curating high-quality scientific relationships from peer-reviewed journals and both public and private biomedical databases. Information collected goes through a thorough, repeatable quality control process to insure the molecular information, called Findings, are captured as originally published and are integrated into QIAGEN’s Ingenuity Ontology, a framework for organizing and describing biological evidence. Both confirmation and contradictory Findings are captured, including the source publication and the context for the Finding, to ensure users will have all the supporting evidence required to assess the applicability of a specific Finding.
Expert Review Process
Our unique knowledge acquisition processes and quality control steps enable the level of structure in the Knowledge Base. All information in the Knowledge Base is manually reviewed by experts to ensure that the content is accurate and detailed, so whether you are using a manually curated relationship from the literature or a relationship described in a third party database, you can trust the quality of information in the Knowledge Base. And you can always link back to the original finding in the original source article.